The intelligence gap between Black and White survey workers on the Prolific platform

Init

library(kirkegaard)

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load_packages(
  haven,
  mirt,
  furrr,
  metafor
)

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plan(multisession)

#furrr bug
options(future.rng.onMisuse="ignore")

Functions

#bootstrapped gap sizes
bootstrap_gaps = function(x, group, n=1000) {
  future_map_dfr(.x = 1:n, .f = function(i) {
    # browser()
    #resample
    i_idx = sample(1:nrow(x), replace = T)
    
    #subset
    i_cog = x[i_idx, ]
    i_group = group[i_idx] %>% factor() %>% fct_relevel("White")
    
    #compute gaps
    i_mirt_fit = mirt(
      data = i_cog,
      model = 1,
      verbose = F
      )
    i_mirt_fit_scores = fscores(i_mirt_fit, full.scores = T, full.scores.SE = T)
    
    i_cog$g = i_mirt_fit_scores[, 1] %>% standardize(i_group == "White")
    
    tibble(
      resample = i,
      reliability = empirical_rxx(i_mirt_fit_scores),
      d = mean(i_cog$g[i_group == "Black"]),
      d_adjusted = d %>% adj_d_reliability(reliability)
    )
    
    }) #end replicates
  
}

Data

d1a = read_sav("data/study 1a - Sentence Verification.sav")
d1b = read_sav("data/study 1b - Synonyms.sav")
d1c = read_sav("data/study 1c - Paper Folding.sav")
d234 = read_sav("data/study_2_3_and_4_experiment_paperfold.sav")

Analysis

Basic

#sample sizes
nrow(d1b)

## [1] 1000

nrow(d1c)

## [1] 1006

nrow(d234)

## [1] 1351

nrow(d234) + nrow(d1b) + nrow(d1c)

## [1] 3357

d1b$Race %>% table2()

d1c$Race %>% table2()

d234$Race %>% table2()

#subset to black-white
d1b_bw = d1b %>% filter(Race %in% c("Black", "White"))
d1c_bw = d1c %>% filter(Race %in% c("Black", "White"))
d234_bw = d234 %>% filter(Race %in% c("Black", "White"))

nrow(d1b_bw)

## [1] 915

nrow(d1c_bw)

## [1] 772

nrow(d234_bw)

## [1] 1239

nrow(d1b_bw) + nrow(d1c_bw) + nrow(d234_bw)

## [1] 2926

#test items
d1a %>% select(baddeley_1:baddeley_32)

Study 1b

d1b_cog = d1b %>% select(SynA1_r:SynA25_r) %>% select(-SynA12_r) %>% map_df(as.numeric)

s1b_mirt_fit = mirt(
  data = d1b_cog,
  model = 1
)

## 
Iteration: 1, Log-Lik: -11426.901, Max-Change: 0.34777
Iteration: 2, Log-Lik: -11377.603, Max-Change: 0.15717
Iteration: 3, Log-Lik: -11369.747, Max-Change: 0.04755
Iteration: 4, Log-Lik: -11368.393, Max-Change: 0.02505
Iteration: 5, Log-Lik: -11368.141, Max-Change: 0.01030
Iteration: 6, Log-Lik: -11368.076, Max-Change: 0.00424
Iteration: 7, Log-Lik: -11368.063, Max-Change: 0.00269
Iteration: 8, Log-Lik: -11368.057, Max-Change: 0.00212
Iteration: 9, Log-Lik: -11368.055, Max-Change: 0.00082
Iteration: 10, Log-Lik: -11368.055, Max-Change: 0.00038
Iteration: 11, Log-Lik: -11368.055, Max-Change: 0.00025
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Iteration: 15, Log-Lik: -11368.055, Max-Change: 0.00041
Iteration: 16, Log-Lik: -11368.055, Max-Change: 0.00008

s1b_mirt_fit %>% summary()

##             F1     h2
## SynA1_r  0.271 0.0732
## SynA2_r  0.196 0.0385
## SynA3_r  0.375 0.1406
## SynA4_r  0.412 0.1695
## SynA5_r  0.421 0.1771
## SynA6_r  0.385 0.1480
## SynA7_r  0.604 0.3653
## SynA8_r  0.463 0.2141
## SynA9_r  0.482 0.2322
## SynA10_r 0.504 0.2544
## SynA11_r 0.353 0.1245
## SynA13_r 0.350 0.1224
## SynA14_r 0.501 0.2513
## SynA15_r 0.620 0.3844
## SynA16_r 0.380 0.1441
## SynA17_r 0.536 0.2872
## SynA18_r 0.382 0.1456
## SynA19_r 0.495 0.2446
## SynA20_r 0.236 0.0558
## SynA21_r 0.351 0.1231
## SynA22_r 0.418 0.1744
## SynA23_r 0.384 0.1473
## SynA24_r 0.313 0.0980
## SynA25_r 0.211 0.0444
## 
## SS loadings:  4.16 
## Proportion Var:  0.173 
## 
## Factor correlations: 
## 
##    F1
## F1  1

s1b_mirt_fit_scores = fscores(s1b_mirt_fit, full.scores = T, full.scores.SE = T)
d1b$g = s1b_mirt_fit_scores[, 1] %>% standardize(d1b$Race == "White")

#reliability
marginal_rxx(s1b_mirt_fit)

## [1] 0.6500301

empirical_rxx(s1b_mirt_fit_scores)

##        F1 
## 0.6545849

#gaps
GG_group_means(d1b, "g", groupvar = "Race")

mean(d1b$g[d1b$Race=="Black"])

## [1] -0.7116957

#adjust for reliability
mean(d1b$g[d1b$Race=="Black"]) %>% adj_d_reliability(empirical_rxx(s1b_mirt_fit_scores))

##         F1 
## -0.9106019

#Jensen method
s1b_items = tibble(
  item = d1b_cog %>% names(),
  loading = s1b_mirt_fit %>% summary() %>% .$rotF %>% as.vector(),
  black_white_d = map_dbl(d1b_cog, function(x) {
    #pass rates
    pass_black = x[d1b$Race == "Black"] %>% wtd_mean()
    pass_white = x[d1b$Race == "White"] %>% wtd_mean()
    
    #inverse normal d value
    qnorm(pass_white) - qnorm(pass_black)
  })
)

##             F1     h2
## SynA1_r  0.271 0.0732
## SynA2_r  0.196 0.0385
## SynA3_r  0.375 0.1406
## SynA4_r  0.412 0.1695
## SynA5_r  0.421 0.1771
## SynA6_r  0.385 0.1480
## SynA7_r  0.604 0.3653
## SynA8_r  0.463 0.2141
## SynA9_r  0.482 0.2322
## SynA10_r 0.504 0.2544
## SynA11_r 0.353 0.1245
## SynA13_r 0.350 0.1224
## SynA14_r 0.501 0.2513
## SynA15_r 0.620 0.3844
## SynA16_r 0.380 0.1441
## SynA17_r 0.536 0.2872
## SynA18_r 0.382 0.1456
## SynA19_r 0.495 0.2446
## SynA20_r 0.236 0.0558
## SynA21_r 0.351 0.1231
## SynA22_r 0.418 0.1744
## SynA23_r 0.384 0.1473
## SynA24_r 0.313 0.0980
## SynA25_r 0.211 0.0444
## 
## SS loadings:  4.16 
## Proportion Var:  0.173 
## 
## Factor correlations: 
## 
##    F1
## F1  1

GG_scatter(s1b_items, "loading", "black_white_d", case_names = "item")

## `geom_smooth()` using formula 'y ~ x'

lm(black_white_d ~ loading, data = s1b_items) %>% predict(newdata = data.frame(loading = 1), interval = "confidence")

##         fit         lwr      upr
## 1 0.6609966 -0.03125876 1.353252

#test bias DIF
DIF_test(
  items = d1b_bw %>% select(!!names(d1b_cog)) %>% map_df(as.numeric),
  model = 1,
  group = d1b_bw$Race
)

## There are 8 steps

## Step 1: Initial joint fit

## 
Iteration: 1, Log-Lik: -10306.411, Max-Change: 0.30639
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## 
## Step 2: Initial MI fit

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Iteration: 494, Log-Lik: -10248.537, Max-Change: 0.00030
Iteration: 495, Log-Lik: -10248.537, Max-Change: 0.00026
Iteration: 496, Log-Lik: -10248.537, Max-Change: 0.00062
Iteration: 497, Log-Lik: -10248.537, Max-Change: 0.00034
Iteration: 498, Log-Lik: -10248.536, Max-Change: 0.00027
Iteration: 499, Log-Lik: -10248.536, Max-Change: 0.00037
Iteration: 500, Log-Lik: -10248.536, Max-Change: 0.00028

## EM cycles terminated after 500 iterations.

## 
## Step 3: Leave one out MI testing

## 
## Step 4: Fit without DIF items, liberal threshold

## 
Iteration: 1, Log-Lik: -10336.432, Max-Change: 0.31336
Iteration: 2, Log-Lik: -10295.675, Max-Change: 0.11270
Iteration: 3, Log-Lik: -10289.460, Max-Change: 0.05017
Iteration: 4, Log-Lik: -10288.339, Max-Change: 0.02195
Iteration: 5, Log-Lik: -10288.111, Max-Change: 0.01271
Iteration: 6, Log-Lik: -10288.058, Max-Change: 0.00613
Iteration: 7, Log-Lik: -10288.048, Max-Change: 0.00408
Iteration: 8, Log-Lik: -10288.043, Max-Change: 0.00186
Iteration: 9, Log-Lik: -10288.042, Max-Change: 0.00104
Iteration: 10, Log-Lik: -10288.041, Max-Change: 0.00070
Iteration: 11, Log-Lik: -10288.041, Max-Change: 0.00029
Iteration: 12, Log-Lik: -10288.041, Max-Change: 0.00023
Iteration: 13, Log-Lik: -10288.041, Max-Change: 0.00101
Iteration: 14, Log-Lik: -10288.041, Max-Change: 0.00016
Iteration: 15, Log-Lik: -10288.041, Max-Change: 0.00013
Iteration: 16, Log-Lik: -10288.041, Max-Change: 0.00037
Iteration: 17, Log-Lik: -10288.041, Max-Change: 0.00010
Iteration: 18, Log-Lik: -10288.041, Max-Change: 0.00006

## 
## Step 5: Fit without DIF items, conservative threshold

## 
Iteration: 1, Log-Lik: -10306.411, Max-Change: 0.30639
Iteration: 2, Log-Lik: -10261.575, Max-Change: 0.12327
Iteration: 3, Log-Lik: -10255.142, Max-Change: 0.04778
Iteration: 4, Log-Lik: -10253.983, Max-Change: 0.02189
Iteration: 5, Log-Lik: -10253.772, Max-Change: 0.00943
Iteration: 6, Log-Lik: -10253.723, Max-Change: 0.00509
Iteration: 7, Log-Lik: -10253.712, Max-Change: 0.00217
Iteration: 8, Log-Lik: -10253.709, Max-Change: 0.00210
Iteration: 9, Log-Lik: -10253.707, Max-Change: 0.00071
Iteration: 10, Log-Lik: -10253.707, Max-Change: 0.00047
Iteration: 11, Log-Lik: -10253.707, Max-Change: 0.00021
Iteration: 12, Log-Lik: -10253.707, Max-Change: 0.00019
Iteration: 13, Log-Lik: -10253.707, Max-Change: 0.00073
Iteration: 14, Log-Lik: -10253.707, Max-Change: 0.00007

## 
## Step 6: Fit with anchor items, liberal threshold

## 
Iteration: 1, Log-Lik: -10306.411, Max-Change: 1.57646
Iteration: 2, Log-Lik: -10251.914, Max-Change: 0.34498
Iteration: 3, Log-Lik: -10245.937, Max-Change: 0.30116
Iteration: 4, Log-Lik: -10244.592, Max-Change: 0.25561
Iteration: 5, Log-Lik: -10244.084, Max-Change: 0.65596
Iteration: 6, Log-Lik: -10243.590, Max-Change: 0.70531
Iteration: 7, Log-Lik: -10242.899, Max-Change: 0.16452
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Iteration: 10, Log-Lik: -10242.467, Max-Change: 0.13871
Iteration: 11, Log-Lik: -10242.425, Max-Change: 0.55973
Iteration: 12, Log-Lik: -10242.375, Max-Change: 0.81358
Iteration: 13, Log-Lik: -10242.302, Max-Change: 0.13906
Iteration: 14, Log-Lik: -10242.255, Max-Change: 0.75707
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Iteration: 18, Log-Lik: -10242.111, Max-Change: 0.18928
Iteration: 19, Log-Lik: -10242.098, Max-Change: 0.45090
Iteration: 20, Log-Lik: -10242.068, Max-Change: 0.07771
Iteration: 21, Log-Lik: -10242.044, Max-Change: 0.93108
Iteration: 22, Log-Lik: -10242.008, Max-Change: 0.76334
Iteration: 23, Log-Lik: -10241.979, Max-Change: 0.08517
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Iteration: 500, Log-Lik: -10238.653, Max-Change: 0.00191

## EM cycles terminated after 500 iterations.

## 
## Step 7: Fit with anchor items, conservative threshold

## 
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Iteration: 367, Log-Lik: -10248.614, Max-Change: 0.00140
Iteration: 368, Log-Lik: -10248.613, Max-Change: 0.00108
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Iteration: 383, Log-Lik: -10248.596, Max-Change: 0.00117
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Iteration: 385, Log-Lik: -10248.595, Max-Change: 0.00121
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Iteration: 387, Log-Lik: -10248.593, Max-Change: 0.00083
Iteration: 388, Log-Lik: -10248.592, Max-Change: 0.00183
Iteration: 389, Log-Lik: -10248.590, Max-Change: 0.00111
Iteration: 390, Log-Lik: -10248.590, Max-Change: 0.00086
Iteration: 391, Log-Lik: -10248.589, Max-Change: 0.00115
Iteration: 392, Log-Lik: -10248.588, Max-Change: 0.00088
Iteration: 393, Log-Lik: -10248.587, Max-Change: 0.00079
Iteration: 394, Log-Lik: -10248.587, Max-Change: 0.00173
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Iteration: 396, Log-Lik: -10248.584, Max-Change: 0.00081
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Iteration: 399, Log-Lik: -10248.582, Max-Change: 0.00075
Iteration: 400, Log-Lik: -10248.582, Max-Change: 0.00163
Iteration: 401, Log-Lik: -10248.580, Max-Change: 0.00099
Iteration: 402, Log-Lik: -10248.579, Max-Change: 0.00077
Iteration: 403, Log-Lik: -10248.579, Max-Change: 0.00103
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Iteration: 405, Log-Lik: -10248.577, Max-Change: 0.00070
Iteration: 406, Log-Lik: -10248.577, Max-Change: 0.00153
Iteration: 407, Log-Lik: -10248.575, Max-Change: 0.00094
Iteration: 408, Log-Lik: -10248.575, Max-Change: 0.00073
Iteration: 409, Log-Lik: -10248.574, Max-Change: 0.00097
Iteration: 410, Log-Lik: -10248.573, Max-Change: 0.00074
Iteration: 411, Log-Lik: -10248.573, Max-Change: 0.00066
Iteration: 412, Log-Lik: -10248.572, Max-Change: 0.00144
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Iteration: 415, Log-Lik: -10248.570, Max-Change: 0.00092
Iteration: 416, Log-Lik: -10248.569, Max-Change: 0.00070
Iteration: 417, Log-Lik: -10248.569, Max-Change: 0.00063
Iteration: 418, Log-Lik: -10248.568, Max-Change: 0.00136
Iteration: 419, Log-Lik: -10248.567, Max-Change: 0.00083
Iteration: 420, Log-Lik: -10248.567, Max-Change: 0.00064
Iteration: 421, Log-Lik: -10248.566, Max-Change: 0.00085
Iteration: 422, Log-Lik: -10248.565, Max-Change: 0.00066
Iteration: 423, Log-Lik: -10248.565, Max-Change: 0.00059
Iteration: 424, Log-Lik: -10248.565, Max-Change: 0.00127
Iteration: 425, Log-Lik: -10248.563, Max-Change: 0.00078
Iteration: 426, Log-Lik: -10248.563, Max-Change: 0.00061
Iteration: 427, Log-Lik: -10248.562, Max-Change: 0.00081
Iteration: 428, Log-Lik: -10248.562, Max-Change: 0.00062
Iteration: 429, Log-Lik: -10248.562, Max-Change: 0.00055
Iteration: 430, Log-Lik: -10248.561, Max-Change: 0.00119
Iteration: 431, Log-Lik: -10248.560, Max-Change: 0.00073
Iteration: 432, Log-Lik: -10248.560, Max-Change: 0.00057
Iteration: 433, Log-Lik: -10248.559, Max-Change: 0.00075
Iteration: 434, Log-Lik: -10248.559, Max-Change: 0.00058
Iteration: 435, Log-Lik: -10248.558, Max-Change: 0.00052
Iteration: 436, Log-Lik: -10248.558, Max-Change: 0.00112
Iteration: 437, Log-Lik: -10248.557, Max-Change: 0.00069
Iteration: 438, Log-Lik: -10248.557, Max-Change: 0.00053
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Iteration: 441, Log-Lik: -10248.555, Max-Change: 0.00049
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Iteration: 464, Log-Lik: -10248.546, Max-Change: 0.00042
Iteration: 465, Log-Lik: -10248.546, Max-Change: 0.00037
Iteration: 466, Log-Lik: -10248.545, Max-Change: 0.00083
Iteration: 467, Log-Lik: -10248.545, Max-Change: 0.00049
Iteration: 468, Log-Lik: -10248.544, Max-Change: 0.00037
Iteration: 469, Log-Lik: -10248.544, Max-Change: 0.00052
Iteration: 470, Log-Lik: -10248.544, Max-Change: 0.00039
Iteration: 471, Log-Lik: -10248.544, Max-Change: 0.00035
Iteration: 472, Log-Lik: -10248.543, Max-Change: 0.00079
Iteration: 473, Log-Lik: -10248.543, Max-Change: 0.00045
Iteration: 474, Log-Lik: -10248.543, Max-Change: 0.00035
Iteration: 475, Log-Lik: -10248.542, Max-Change: 0.00048
Iteration: 476, Log-Lik: -10248.542, Max-Change: 0.00037
Iteration: 477, Log-Lik: -10248.542, Max-Change: 0.00032
Iteration: 478, Log-Lik: -10248.542, Max-Change: 0.00074
Iteration: 479, Log-Lik: -10248.541, Max-Change: 0.00042
Iteration: 480, Log-Lik: -10248.541, Max-Change: 0.00033
Iteration: 481, Log-Lik: -10248.541, Max-Change: 0.00045
Iteration: 482, Log-Lik: -10248.540, Max-Change: 0.00034
Iteration: 483, Log-Lik: -10248.540, Max-Change: 0.00030
Iteration: 484, Log-Lik: -10248.540, Max-Change: 0.00071
Iteration: 485, Log-Lik: -10248.539, Max-Change: 0.00040
Iteration: 486, Log-Lik: -10248.539, Max-Change: 0.00031
Iteration: 487, Log-Lik: -10248.539, Max-Change: 0.00043
Iteration: 488, Log-Lik: -10248.539, Max-Change: 0.00032
Iteration: 489, Log-Lik: -10248.539, Max-Change: 0.00028
Iteration: 490, Log-Lik: -10248.538, Max-Change: 0.00066
Iteration: 491, Log-Lik: -10248.538, Max-Change: 0.00037
Iteration: 492, Log-Lik: -10248.538, Max-Change: 0.00029
Iteration: 493, Log-Lik: -10248.538, Max-Change: 0.00039
Iteration: 494, Log-Lik: -10248.537, Max-Change: 0.00030
Iteration: 495, Log-Lik: -10248.537, Max-Change: 0.00026
Iteration: 496, Log-Lik: -10248.537, Max-Change: 0.00062
Iteration: 497, Log-Lik: -10248.537, Max-Change: 0.00034
Iteration: 498, Log-Lik: -10248.536, Max-Change: 0.00027
Iteration: 499, Log-Lik: -10248.536, Max-Change: 0.00037
Iteration: 500, Log-Lik: -10248.536, Max-Change: 0.00028

## EM cycles terminated after 500 iterations.

## 
## Step 8: Get scores

## $scores
## $scores$original
##                   F1     SE_F1
##   [1,] -0.3038239606 0.5531481
##   [2,] -1.4032538443 0.4956733
##   [3,] -0.5038713617 0.5397761
##   [4,]  0.1723240678 0.5887213
##   [5,]  0.4890588878 0.6147293
##   [6,] -0.2404759056 0.5575934
##   [7,]  0.9604925031 0.6558389
##   [8,]  0.7803118949 0.6398643
##   [9,] -1.3372966608 0.4978182
##  [10,] -0.2127895394 0.5595663
##  [11,] -1.3901213766 0.4960843
##  [12,] -0.7287094618 0.5260831
##  [13,] -1.7743846504 0.4875754
##  [14,] -1.4634843568 0.4938926
##  [15,]  0.1785875450 0.5892195
##  [16,] -0.3010960305 0.5533375
##  [17,] -0.3810872446 0.5478601
##  [18,] -0.5570192668 0.5364050
##  [19,] -0.5415121049 0.5373803
##  [20,] -0.6216039722 0.5324179
##  [21,]  0.9349794124 0.6535616
##  [22,] -0.7562101282 0.5245147
##  [23,]  0.1637489176 0.5880403
##  [24,] -0.4934459066 0.5404466
##  [25,] -1.9275623674 0.4863404
##  [26,]  1.2240929276 0.6795758
##  [27,] -0.0130123290 0.5743108
##  [28,] -0.7085124670 0.5272504
##  [29,]  0.1206013784 0.5846340
##  [30,] -0.6231618038 0.5323233
##  [31,]  0.0057566309 0.5757396
##  [32,] -1.0851837220 0.5077808
##  [33,] -1.1840220722 0.5035546
##  [34,]  0.7539795570 0.6375534
##  [35,] -1.2247180210 0.5019321
##  [36,]  0.1937026721 0.5904248
##  [37,]  1.3512034830 0.6911023
##  [38,] -0.2721049954 0.5553618
##  [39,] -0.5469987641 0.5370344
##  [40,]  0.9351952667 0.6535809
##  [41,] -0.8055210954 0.5217643
##  [42,]  0.5957631552 0.6238217
##  [43,]  0.8897795542 0.6495386
##  [44,]  0.7578066662 0.6378888
##  [45,] -0.2982307379 0.5535367
##  [46,] -0.6201954969 0.5325035
##  [47,] -0.0233601432 0.5735261
##  [48,]  1.4808958937 0.7028702
##  [49,] -0.3684751603 0.5487129
##  [50,]  0.1553211899 0.5873723
##  [51,]  1.6715601293 0.7201100
##  [52,] -1.3152719052 0.4985788
##  [53,] -0.7348940967 0.5257283
##  [54,] -0.0862084072 0.5688081
##  [55,] -0.3848396001 0.5476071
##  [56,] -1.2494162031 0.5009819
##  [57,]  0.0430812162 0.5786021
##  [58,]  1.1828278447 0.6758409
##  [59,] -0.1424752209 0.5646560
##  [60,] -1.8280555203 0.4869970
##  [61,] -0.4282383272 0.5447081
##  [62,]  0.1512513950 0.5870502
##  [63,]  0.1507665430 0.5870118
##  [64,] -1.1305623603 0.5057911
##  [65,] -0.2412433295 0.5575390
##  [66,] -0.8885529419 0.5173182
##  [67,]  0.1108799287 0.5838713
##  [68,] -1.5601332662 0.4914024
##  [69,]  0.0340082932 0.5779038
##  [70,]  1.3348304315 0.6896165
##  [71,] -0.3586723080 0.5493787
##  [72,] -0.2448321493 0.5572847
##  [73,] -0.2682455963 0.5556328
##  [74,]  0.0365654966 0.5781004
##  [75,]  0.8602413468 0.6469181
##  [76,] -0.1438631962 0.5645544
##  [77,]  0.1287631874 0.5852757
##  [78,] -1.0837953871 0.5078430
##  [79,]  1.6715601293 0.7201100
##  [80,]  0.7665367327 0.6386546
##  [81,]  0.4062219334 0.6077772
##  [82,]  0.2575624543 0.5955610
##  [83,] -1.0109482086 0.5112108
##  [84,] -0.2511861596 0.5568351
##  [85,]  0.5979417627 0.6240089
##  [86,]  0.0142182841 0.5763861
##  [87,] -1.2680375688 0.5002830
##  [88,]  0.7059104008 0.6333526
##  [89,] -0.5298990058 0.5381152
##  [90,] -0.0153820324 0.5741309
##  [91,] -1.3108249380 0.4987350
##  [92,] -0.6429949959 0.5311246
##  [93,]  0.0447892956 0.5787338
##  [94,] -0.4848886220 0.5409993
##  [95,] -0.6659891534 0.5297498
##  [96,]  0.2655175778 0.5962057
##  [97,]  0.1264868340 0.5850966
##  [98,] -1.2929572656 0.4993716
##  [99,]  0.9983068223 0.6592222
## [100,] -0.5594161928 0.5362548
## [101,] -0.0333017179 0.5727743
## [102,]  0.1665503002 0.5882626
## [103,]  0.9604925031 0.6558389
## [104,] -1.8883709450 0.4865341
## [105,] -0.2172590454 0.5592466
## [106,]  0.6269869437 0.6265093
## [107,]  0.0713287759 0.5807867
## [108,]  0.0836522417 0.5817446
## [109,] -1.3098514366 0.4987693
## [110,]  0.9191602488 0.6521519
## [111,]  0.2728812096 0.5968034
## [112,]  0.4495368744 0.6114002
## [113,]  0.6763257227 0.6307793
## [114,] -0.8650235187 0.5185540
## [115,] -0.1589224009 0.5634554
## [116,] -1.3147302358 0.4985977
## [117,] -0.6627061346 0.5299451
## [118,] -0.9988151442 0.5117916
## [119,]  0.0824721233 0.5816528
## [120,] -0.2677983560 0.5556643
## [121,] -0.2398427383 0.5576384
## [122,] -0.8190828908 0.5210220
## [123,]  0.8394012183 0.6450735
## [124,] -1.5113119047 0.4926029
## [125,]  0.3224144560 0.6008471
## [126,]  0.2420664175 0.5943082
## [127,] -0.0628638527 0.5705509
## [128,] -1.1023530732 0.5070183
## [129,]  1.3639252904 0.6922569
## [130,] -0.6990034983 0.5278044
## [131,] -0.4118539639 0.5457968
## [132,]  0.6107353955 0.6251090
## [133,] -0.1311662359 0.5654849
## [134,]  0.2006545447 0.5909805
## [135,]  0.3272255683 0.6012420
## [136,] -0.6177296045 0.5326536
## [137,]  0.6221785745 0.6260947
## [138,] -1.2048361880 0.5027160
## [139,] -0.6330899549 0.5317217
## [140,] -0.5561586886 0.5364589
## [141,]  0.2953615025 0.5986337
## [142,]  0.6112597479 0.6251541
## [143,]  0.3091583925 0.5997610
## [144,] -1.5640722217 0.4913107
## [145,]  1.2240929276 0.6795758
## [146,] -0.0552228167 0.5711238
## [147,]  1.1875791693 0.6762707
## [148,] -0.7573257307 0.5244516
## [149,] -0.4930436028 0.5404726
## [150,]  0.5873409896 0.6230988
## [151,] -0.9541698019 0.5139758
## [152,]  0.4664435452 0.6128217
## [153,]  1.1501564652 0.6728876
## [154,]  1.3512034830 0.6911023
## [155,] -0.1570271322 0.5635934
## [156,] -0.3935242505 0.5470231
## [157,] -0.5528381390 0.5366673
## [158,]  1.6715601293 0.7201100
## [159,]  1.6715601293 0.7201100
## [160,] -0.0072132819 0.5747515
## [161,] -0.3097062011 0.5527402
## [162,]  0.2202932469 0.5925549
## [163,] -0.4795360144 0.5413460
## [164,] -0.1682509662 0.5627772
## [165,]  0.0430812162 0.5786021
## [166,]  0.4646253469 0.6126686
## [167,]  1.3512034830 0.6911023
## [168,]  0.0947914116 0.5826130
## [169,] -0.5105018380 0.5393512
## [170,] -1.3409696324 0.4976935
## [171,]  1.6715601293 0.7201100
## [172,]  1.0522517779 0.6640636
## [173,]  0.3091583925 0.5997610
## [174,]  0.1713670709 0.5886452
## [175,] -0.3312741081 0.5512522
## [176,] -1.7899624016 0.4873915
## [177,] -0.8186419955 0.5210460
## [178,] -0.6944685178 0.5280696
## [179,] -0.6345487259 0.5316336
## [180,]  0.3993966239 0.6072088
## [181,]  0.6559370216 0.6290114
## [182,]  0.7059104008 0.6333526
## [183,]  0.6064667849 0.6247417
## [184,]  1.1818218970 0.6757499
## [185,]  0.3549951653 0.6035284
## [186,] -1.6546074297 0.4894207
## [187,]  0.4211591572 0.6090235
## [188,]  1.1818218970 0.6757499
## [189,] -0.6253888427 0.5321881
## [190,] -0.0481545510 0.5716549
## [191,] -0.5048781596 0.5397115
## [192,] -0.5144625890 0.5390980
## [193,] -0.0681341628 0.5701564
## [194,] -0.5207131834 0.5386992
## [195,]  0.1765609804 0.5890583
## [196,] -0.4193174139 0.5453000
## [197,] -0.8164090403 0.5211678
## [198,] -0.0352058924 0.5726306
## [199,] -1.0144190990 0.5110457
## [200,]  0.7720156450 0.6391355
## [201,]  0.7664809785 0.6386497
## [202,] -0.4867673779 0.5408778
## [203,]  0.2095141340 0.5916899
## [204,] -1.0202270810 0.5107705
## [205,] -0.1546324415 0.5637680
## [206,] -0.3437265406 0.5503983
## [207,] -1.0662158104 0.5086368
## [208,]  0.5941177404 0.6236804
## [209,] -0.9838270194 0.5125166
## [210,]  0.2054016223 0.5913605
## [211,]  0.6734623210 0.6305307
## [212,] -1.6274002014 0.4899446
## [213,] -0.1586949750 0.5634720
## [214,]  0.6889797363 0.6318788
## [215,]  0.7461793841 0.6368701
## [216,]  0.5339932137 0.6185402
## [217,] -0.3624728838 0.5491203
## [218,]  0.2982633951 0.5988705
## [219,]  0.8631360327 0.6471746
## [220,] -0.1481218927 0.5642431
## [221,]  0.7408254067 0.6364015
## [222,] -0.0293001789 0.5730767
## [223,]  0.8228327504 0.6436097
## [224,]  0.8602413468 0.6469181
## [225,]  0.2830708678 0.5976320
## [226,]  0.1109006035 0.5838729
## [227,] -1.2133031526 0.5023801
## [228,]  0.0394062959 0.5783191
## [229,]  0.0958772777 0.5826978
## [230,] -0.6649414060 0.5298121
## [231,]  0.5319670950 0.6183678
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## [655,]  1.2240929276 0.6795758
## [656,]  0.5760347120 0.6221297
## [657,] -1.8586672379 0.4867372
## [658,]  0.9494974008 0.6548569
## [659,] -1.2907509133 0.4994511
## [660,]  0.7256207844 0.6350723
## [661,]  0.5522846608 0.6200992
## [662,]  0.9234544205 0.6525344
## [663,] -0.0158043033 0.5740989
## [664,] -0.8792832689 0.5178027
## [665,]  0.6186389289 0.6257896
## [666,] -0.0600416671 0.5707624
## [667,]  0.8507904967 0.6460812
## [668,] -0.6935483532 0.5281235
## [669,]  0.4601756051 0.6122942
## [670,]  1.4428250503 0.6994171
## [671,] -1.4689469135 0.4937397
## [672,]  0.7986798917 0.6414802
## [673,]  0.8185773726 0.6432342
## [674,] -1.8686651020 0.4866634
## [675,]  0.1649777366 0.5881378
## [676,] -0.5489814932 0.5369097
## [677,] -0.7721475963 0.5236170
## [678,]  0.4857633418 0.6144509
## [679,] -0.1074617066 0.5672317
## [680,] -1.1409669005 0.5053466
## [681,]  0.0427514134 0.5785767
## [682,] -0.7290553696 0.5260632
## [683,]  0.7664809785 0.6386497
## [684,]  0.7492622992 0.6371401
## [685,]  0.9440987735 0.6543751
## [686,] -1.8044803567 0.4872319
## [687,] -0.1761618856 0.5622036
## [688,]  0.6446412257 0.6280340
## [689,]  0.9680810154 0.6565171
## [690,]  0.9800318772 0.6575860
## [691,]  1.0412537835 0.6630752
## [692,]  0.3616748623 0.6040801
## [693,]  0.0940641281 0.5825562
## [694,] -1.4385962617 0.4946075
## [695,] -0.6268726650 0.5320981
## [696,]  0.4926146552 0.6150299
## [697,]  1.6715601293 0.7201100
## [698,]  0.3408260456 0.6023603
## [699,] -0.2025562816 0.5603000
## [700,] -0.5355569512 0.5377567
## [701,] -0.3822886765 0.5477790
## [702,]  0.6107353955 0.6251090
## [703,]  1.3512034830 0.6911023
## [704,]  0.7995863869 0.6415601
## [705,]  0.4393531360 0.6105460
## [706,]  0.2674849864 0.5963653
## [707,] -0.1631784436 0.5631457
## [708,] -0.6669296063 0.5296939
## [709,]  1.6715601293 0.7201100
## [710,]  1.6715601293 0.7201100
## [711,] -0.3347271027 0.5510150
## [712,]  1.3271334049 0.6889180
## [713,] -0.3398514403 0.5506636
## [714,] -0.7160170469 0.5268151
## [715,] -0.7216447719 0.5264899
## [716,] -0.5191480338 0.5387990
## [717,]  0.1524751842 0.5871470
## [718,] -0.1581886365 0.5635088
## [719,] -0.4197788081 0.5452693
## [720,] -0.4049904105 0.5462549
## [721,]  1.3639252904 0.6922569
## [722,] -0.4378795437 0.5440708
## [723,] -0.1210493820 0.5662289
## [724,]  1.1660635086 0.6743251
## [725,] -0.2800493880 0.5548051
## [726,] -0.3290104483 0.5514078
## [727,] -0.8637387192 0.5186220
## [728,]  0.4806717123 0.6140210
## [729,]  1.6715601293 0.7201100
## [730,]  0.4241249445 0.6092714
## [731,] -0.1999566959 0.5604868
## [732,]  1.4231707262 0.6976337
## [733,] -0.5713880572 0.5355074
## [734,] -0.7589661338 0.5243589
## [735,] -0.5065648523 0.5396033
## [736,] -0.0918152737 0.5683913
## [737,]  0.1187887707 0.5844917
## [738,]  0.3274099324 0.6012572
## [739,] -0.8649883226 0.5185558
## [740,] -0.2547636410 0.5565824
## [741,] -2.2849635212 0.4885314
## [742,]  0.7066416264 0.6334164
## [743,]  0.5722815375 0.6218083
## [744,] -0.8487247328 0.5194213
## [745,]  1.1598097493 0.6737599
## [746,]  0.0773935628 0.5812578
## [747,]  1.6715601293 0.7201100
## [748,]  1.0387464267 0.6628500
## [749,] -0.1633818128 0.5631309
## [750,] -0.7291032822 0.5260605
## [751,]  0.7390579835 0.6362469
## [752,] -1.3034607171 0.4989956
## [753,]  0.4889354597 0.6147189
## [754,]  0.7788393119 0.6397349
## [755,] -0.4002705933 0.5465707
## [756,]  1.3639252904 0.6922569
## [757,] -0.4809661146 0.5412533
## [758,]  0.3697811570 0.6047507
## [759,]  0.5858177871 0.6229681
## [760,] -0.3196454526 0.5520531
## [761,] -0.7187621874 0.5266564
## [762,]  0.0713726067 0.5807901
## [763,] -1.2526247647 0.5008604
## [764,]  0.0720076081 0.5808394
## [765,] -0.5939783711 0.5341084
## [766,]  1.2240929276 0.6795758
## [767,] -0.0599432036 0.5707698
## [768,] -0.3742854937 0.5483195
## [769,]  0.3072221332 0.5996026
## [770,]  0.1940166322 0.5904499
## [771,]  0.2570349778 0.5955183
## [772,]  1.2441086323 0.6813890
## [773,]  0.6219355841 0.6260737
## [774,] -0.4490273536 0.5433370
## [775,] -0.2307991230 0.5582809
## [776,] -0.5003201662 0.5400042
## [777,]  1.4808958937 0.7028702
## [778,] -0.2511861596 0.5568351
## [779,] -0.4236277851 0.5450137
## [780,]  0.8271415022 0.6439902
## [781,]  1.1875791693 0.6762707
## [782,]  1.3068669338 0.6870793
## [783,] -0.3027437817 0.5532231
## [784,] -0.6156247405 0.5327819
## [785,] -0.9263656732 0.5153732
## [786,] -0.5271374063 0.5382905
## [787,]  1.0217684208 0.6613257
## [788,]  1.3519745526 0.6911723
## [789,] -0.1371880440 0.5650432
## [790,] -0.3537896095 0.5497112
## [791,]  0.0380778025 0.5782168
## [792,]  1.3068669338 0.6870793
## [793,]  0.4857633418 0.6144509
## [794,]  1.6715601293 0.7201100
## [795,]  1.0384178005 0.6628205
## [796,]  1.0476703638 0.6636518
## [797,]  0.8190718106 0.6432778
## [798,]  0.2830708678 0.5976320
## [799,] -0.5469758527 0.5370359
## [800,]  0.5533869746 0.6201932
## [801,] -0.5988821265 0.5338067
## [802,]  1.1447500576 0.6723993
## [803,] -0.0258358183 0.5733387
## [804,] -0.3910091603 0.5471920
## [805,]  1.1341241089 0.6714398
## [806,]  0.8502564765 0.6460339
## [807,]  0.8785778656 0.6485440
## [808,] -0.5512461534 0.5367673
## [809,] -1.9554857019 0.4862543
## [810,] -0.1940729323 0.5609101
## [811,] -0.2020708986 0.5603349
## [812,]  0.2439173939 0.5944576
## [813,]  0.2274383556 0.5931294
## [814,]  0.5615167677 0.6208876
## [815,] -0.7143107173 0.5269139
## [816,]  0.0559656551 0.5795966
## [817,]  0.2506384240 0.5950007
## [818,]  0.0344766566 0.5779398
## [819,] -0.4701148774 0.5419581
## [820,] -1.1946282419 0.5031250
## [821,]  0.3490986843 0.6030419
## [822,]  0.1686108111 0.5884262
## [823,] -0.4754634158 0.5416103
## [824,]  1.6715601293 0.7201100
## [825,]  0.3216193486 0.6007819
## [826,] -0.0021272001 0.5751386
## [827,] -0.4249838657 0.5449238
## [828,]  0.5150073368 0.6169267
## [829,]  0.5269435659 0.6179406
## [830,] -0.3899986006 0.5472599
## [831,] -0.9112527008 0.5161444
## [832,]  1.0927209848 0.6677058
## [833,]  1.6715601293 0.7201100
## [834,]  1.4703910725 0.7019176
## [835,]  1.0183874537 0.6610224
## [836,]  1.6715601293 0.7201100
## [837,]  0.7849112442 0.6402687
## [838,]  0.5923456225 0.6235283
## [839,]  0.2779071403 0.5972119
## [840,] -0.3802434478 0.5479170
## [841,]  1.1598097493 0.6737599
## [842,] -0.2989727947 0.5534851
## [843,]  0.4062219334 0.6077772
## [844,]  0.6161668004 0.6255766
## [845,] -1.0464675543 0.5095430
## [846,]  1.4808958937 0.7028702
## [847,]  1.6715601293 0.7201100
## [848,] -0.4097983128 0.5459339
## [849,] -0.3048080622 0.5530798
## [850,] -0.7362043745 0.5256533
## [851,]  0.3688451172 0.6046732
## [852,] -0.5648312677 0.5359163
## [853,] -0.5707563617 0.5355467
## [854,]  0.0743945199 0.5810247
## [855,] -0.2596008798 0.5562412
## [856,] -0.3117581966 0.5525982
## [857,] -0.4451711038 0.5435905
## [858,] -0.9629005817 0.5135429
## [859,]  0.3402019952 0.6023089
## [860,] -1.1831257569 0.5035911
## [861,]  0.6648121012 0.6297804
## [862,] -0.2381602845 0.5577578
## [863,]  0.2324338148 0.5935315
## [864,]  0.2643314436 0.5961095
## [865,]  0.6204248644 0.6259435
## [866,] -0.7549292123 0.5245872
## [867,] -0.8415254737 0.5198073
## [868,]  0.6223926701 0.6261131
## [869,]  1.4808958937 0.7028702
## [870,] -1.5579153495 0.4914544
## [871,]  0.6592364210 0.6292972
## [872,]  0.3760115030 0.6052667
## [873,]  1.3589467658 0.6918051
## [874,]  0.2006545447 0.5909805
## [875,] -0.3651071419 0.5489414
## [876,]  0.5363317504 0.6187393
## [877,]  1.3639252904 0.6922569
## [878,] -0.4754456257 0.5416115
## [879,] -0.6491462741 0.5307552
## [880,]  0.1311510553 0.5854637
## [881,]  0.7663040587 0.6386342
## [882,]  0.4610014805 0.6123637
## [883,]  0.2161642793 0.5922233
## [884,]  1.2240929276 0.6795758
## [885,] -0.1714825076 0.5625427
## [886,]  0.4360561904 0.6102698
## [887,]  0.9328213159 0.6533692
## [888,] -0.2344412109 0.5580219
## [889,]  0.4360561904 0.6102698
## [890,] -0.3971638335 0.5467789
## [891,]  1.0098808776 0.6602595
## [892,] -0.0504525379 0.5714822
## [893,]  0.9234544205 0.6525344
## [894,]  0.3743915393 0.6051325
## [895,] -0.4282383272 0.5447081
## [896,]  1.6715601293 0.7201100
## [897,]  0.0571114789 0.5796852
## [898,]  0.1507665430 0.5870118
## [899,]  0.3962643625 0.6069482
## [900,]  1.2441086323 0.6813890
## [901,] -1.0367574551 0.5099942
## [902,] -0.0232867397 0.5735317
## [903,] -0.8636190758 0.5186283
## [904,]  0.9089134862 0.6512398
## [905,]  0.8076268680 0.6422685
## [906,] -2.0844939009 0.4864208
## [907,]  0.1677068685 0.5883544
## [908,] -0.2225146569 0.5588713
## [909,] -0.0418706500 0.5721280
## [910,]  0.5319345889 0.6183651
## [911,]  1.1501564652 0.6728876
## [912,] -0.4929853109 0.5404763
## [913,]  0.8785778656 0.6485440
## [914,] -0.4427648829 0.5437488
## [915,]  0.0995441598 0.5829842
## 
## $scores$noDIF_liberal
##                  F1     SE_F1
##   [1,] -0.188663558 0.5756419
##   [2,] -1.344906836 0.5108621
##   [3,] -0.398810586 0.5608674
##   [4,]  0.086509429 0.5963984
##   [5,]  0.398392692 0.6214913
##   [6,] -0.120321090 0.5806581
##   [7,]  0.886387038 0.6631048
##   [8,]  0.718466036 0.6485416
##   [9,] -1.281369030 0.5131419
##  [10,]  0.135072990 0.6002061
##  [11,] -1.511273549 0.5058042
##  [12,] -0.832675499 0.5340661
##  [13,] -1.749024084 0.5010379
##  [14,] -1.405923457 0.5088506
##  [15,]  0.360804489 0.6183923
##  [16,] -0.398587819 0.5608825
##  [17,] -0.257070331 0.5707212
##  [18,] -0.432772084 0.5585791
##  [19,] -0.437452431 0.5582660
##  [20,] -0.514233907 0.5532121
##  [21,]  1.162996760 0.6874236
##  [22,] -0.868591417 0.5321097
##  [23,]  0.073277366 0.5953679
##  [24,] -0.594336113 0.5481106
##  [25,] -2.063506123 0.4995589
##  [26,]  1.173672145 0.6883669
##  [27,] -0.106752191 0.5816655
##  [28,] -0.616218947 0.5467486
##  [29,]  0.038664600 0.5926869
##  [30,] -0.722913786 0.5403124
##  [31,]  0.132526991 0.6000055
##  [32,] -1.015435211 0.5245909
##  [33,] -1.273145514 0.5134505
##  [34,]  0.990896121 0.6722569
##  [35,] -1.160086553 0.5179954
##  [36,]  0.128453071 0.5996847
##  [37,]  1.285625497 0.6982668
##  [38,] -0.376620249 0.5623782
##  [39,] -0.645496097 0.5449483
##  [40,]  0.848334556 0.6597876
##  [41,] -0.707092070 0.5412448
##  [42,]  0.508878861 0.6307030
##  [43,]  0.807921154 0.6562748
##  [44,]  0.687046510 0.6458408
##  [45,] -0.426853114 0.5589758
##  [46,] -0.508085564 0.5536111
##  [47,] -0.128926322 0.5800212
##  [48,]  1.406647334 0.7089668
##  [49,] -0.455822532 0.5570428
##  [50,]  0.063046168 0.5945732
##  [51,]  1.616377520 0.7274281
##  [52,] -1.253871474 0.5141856
##  [53,] -0.629465427 0.5459309
##  [54,]  0.060755706 0.5943956
##  [55,] -0.258712683 0.5706043
##  [56,] -1.174763031 0.5173742
##  [57,]  0.174971775 0.6033638
##  [58,]  1.113222485 0.6830284
##  [59,] -0.245493366 0.5715467
##  [60,] -1.969170693 0.4994049
##  [61,] -0.533830797 0.5519476
##  [62,]  0.326298035 0.6155640
##  [63,]  0.056554595 0.5940700
##  [64,] -1.247696330 0.5144246
##  [65,] -0.354821427 0.5638741
##  [66,] -0.808201540 0.5354244
##  [67,]  0.027131800 0.5917984
##  [68,] -1.700429846 0.5017653
##  [69,] -0.057408580 0.5853600
##  [70,]  1.274939333 0.6973216
##  [71,] -0.238923801 0.5720165
##  [72,] -0.324494787 0.5659744
##  [73,] -0.374646278 0.5625132
##  [74,]  0.190436050 0.6045945
##  [75,]  0.794739432 0.6551315
##  [76,] -0.008506558 0.5890679
##  [77,]  0.274290755 0.6113328
##  [78,] -1.019777213 0.5243809
##  [79,]  1.616377520 0.7274281
##  [80,]  0.684087287 0.6455869
##  [81,]  0.300134110 0.6134305
##  [82,]  0.186918942 0.6043143
##  [83,] -1.140394621 0.5188431
##  [84,] -0.350841639 0.5641485
##  [85,]  0.506662574 0.6305168
##  [86,]  0.159116618 0.6021059
##  [87,] -1.212096888 0.5158355
##  [88,]  0.624122781 0.6404585
##  [89,] -0.633283485 0.5456962
##  [90,] -0.112729821 0.5812213
##  [91,] -1.262048601 0.5138717
##  [92,] -0.535817023 0.5518200
##  [93,]  0.212789462 0.6063803
##  [94,] -0.387243288 0.5616534
##  [95,] -0.768436728 0.5376740
##  [96,]  0.182649318 0.6039743
##  [97,]  0.048987513 0.5934843
##  [98,] -1.069247273 0.5220392
##  [99,]  0.901289136 0.6644063
## [100,] -0.642558053 0.5451278
## [101,] -0.131333853 0.5798433
## [102,]  0.062259884 0.5945123
## [103,]  0.886387038 0.6631048
## [104,] -1.679585134 0.5021169
## [105,] -0.320106275 0.5662801
## [106,]  0.828709924 0.6580804
## [107,] -0.021079567 0.5881102
## [108,] -0.039986512 0.5866757
## [109,] -1.439505484 0.5078200
## [110,]  0.818644470 0.6572058
## [111,]  0.476561762 0.6279934
## [112,]  0.654618160 0.6430624
## [113,]  0.577892472 0.6365283
## [114,] -0.789698780 0.5364647
## [115,] -0.025571924 0.5877688
## [116,] -1.251180516 0.5142896
## [117,] -0.549039128 0.5509735
## [118,] -1.107706717 0.5202859
## [119,]  0.229707478 0.6077369
## [120,] -0.150970642 0.5783964
## [121,] -0.331586485 0.5654813
## [122,] -0.918376983 0.5294725
## [123,]  1.082156643 0.6802882
## [124,] -1.466916877 0.5070197
## [125,]  0.231489593 0.6078801
## [126,]  0.415731034 0.6229269
## [127,] -0.155607372 0.5780560
## [128,] -1.227250260 0.5152281
## [129,]  1.303745411 0.6998696
## [130,] -0.610214350 0.5471209
## [131,] -0.295875517 0.5679764
## [132,]  0.540005003 0.6333239
## [133,] -0.229295533 0.5727067
## [134,]  0.110673096 0.5982880
## [135,]  0.523929014 0.6319689
## [136,] -0.502457092 0.5539771
## [137,]  0.561121075 0.6351080
## [138,] -1.330403232 0.5113661
## [139,] -0.756825236 0.5383407
## [140,] -0.663289497 0.5438666
## [141,]  0.182969809 0.6039998
## [142,]  0.552673082 0.6343936
## [143,]  0.221855058 0.6071067
## [144,] -1.337000552 0.5111356
## [145,]  1.173672145 0.6883669
## [146,]  0.090914960 0.5967422
## [147,]  1.109447016 0.6826952
## [148,] -0.870610482 0.5320011
## [149,] -0.561797213 0.5501613
## [150,]  0.497233899 0.6297252
## [151,] -1.063059453 0.5223268
## [152,]  0.380339133 0.6200005
## [153,]  1.075007290 0.6796580
## [154,]  1.285625497 0.6982668
## [155,] -0.025140967 0.5878015
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## [584,] -0.082222213 0.5834961
## [585,] -0.695729958 0.5419192
## [586,] -0.971830960 0.5267405
## [587,] -0.879374011 0.5315311
## [588,]  0.447855518 0.6255969
## [589,] -0.866114810 0.5322432
## [590,] -0.034979631 0.5870550
## [591,] -0.408098667 0.5602387
## [592,] -1.137265825 0.5189793
## [593,] -0.028190620 0.5875699
## [594,]  0.063882236 0.5946381
## [595,]  1.005369231 0.6735285
## [596,] -0.896955335 0.5305965
## [597,] -1.869111366 0.4998051
## [598,] -0.930939741 0.5288210
## [599,]  0.069465967 0.5950717
## [600,]  0.670842544 0.6444513
## [601,]  0.711670682 0.6479568
## [602,]  0.807921154 0.6562748
## [603,] -0.172053164 0.5768521
## [604,] -1.071483382 0.5219356
## [605,]  0.015478864 0.5909030
## [606,]  0.912429702 0.6653800
## [607,] -0.845287299 0.5333741
## [608,]  0.366224080 0.6188379
## [609,]  1.274939333 0.6973216
## [610,] -0.616746017 0.5467160
## [611,]  0.613886760 0.6395864
## [612,]  0.215396818 0.6065891
## [613,]  0.066145289 0.5948138
## [614,] -0.470942788 0.5560425
## [615,]  0.124634250 0.5993843
## [616,] -1.122159448 0.5196426
## [617,]  0.111336730 0.5983401
## [618,]  0.113526863 0.5985118
## [619,]  0.997160445 0.6728072
## [620,]  0.505741521 0.6304394
## [621,]  0.523929014 0.6319689
## [622,]  0.462323338 0.6268035
## [623,] -0.459778482 0.5567805
## [624,] -0.518280343 0.5529502
## [625,] -0.183055881 0.5760498
## [626,]  0.174971775 0.6033638
## [627,] -0.081935511 0.5835176
## [628,] -0.751994735 0.5386193
## [629,] -0.630230224 0.5458839
## [630,]  1.072013279 0.6793941
## [631,] -0.236508051 0.5721895
## [632,] -0.155865085 0.5780371
## [633,] -0.775819489 0.5372524
## [634,] -1.502327198 0.5060414
## [635,] -0.263646690 0.5702536
## [636,]  0.783284242 0.6541389
## [637,] -1.549673277 0.5048326
## [638,] -1.447886697 0.5075713
## [639,] -0.515921091 0.5531029
## [640,] -0.279218678 0.5691504
## [641,]  1.616377520 0.7274281
## [642,] -1.489750009 0.5063817
## [643,]  0.585650812 0.6371864
## [644,]  1.399015062 0.7082925
## [645,] -0.044433392 0.5863393
## [646,]  0.069535777 0.5950771
## [647,] -0.803420010 0.5356922
## [648,] -1.177600079 0.5172552
## [649,]  0.373851476 0.6194658
## [650,] -0.265851907 0.5700970
## [651,] -0.248264505 0.5713488
## [652,] -1.207087603 0.5160384
## [653,]  1.194407600 0.6901996
## [654,]  1.616377520 0.7274281
## [655,]  1.173672145 0.6883669
## [656,]  0.496256409 0.6296432
## [657,] -2.009971786 0.4994079
## [658,]  0.893156336 0.6636958
## [659,] -1.234802503 0.5149292
## [660,]  0.630469629 0.6409997
## [661,]  0.465505719 0.6270692
## [662,]  0.867245008 0.6614350
## [663,]  0.130098587 0.5998143
## [664,] -0.982163886 0.5262246
## [665,]  0.822133408 0.6575089
## [666,] -0.114894571 0.5810606
## [667,]  0.759536029 0.6520843
## [668,] -0.793226119 0.5362655
## [669,]  0.377531271 0.6197690
## [670,]  1.395763512 0.7080052
## [671,] -1.592312204 0.5038430
## [672,]  0.724295922 0.6490437
## [673,]  0.738081059 0.6502319
## [674,] -1.826663373 0.5001480
## [675,]  0.081517148 0.5960093
## [676,] -0.438328357 0.5582075
## [677,] -0.686656911 0.5424606
## [678,]  0.687046510 0.6458408
## [679,]  0.040790990 0.5928510
## [680,] -0.901693038 0.5303465
## [681,] -0.068944535 0.5844920
## [682,] -0.849376210 0.5331509
## [683,]  0.693391521 0.6463855
## [684,]  0.687915434 0.6459154
## [685,]  0.888362698 0.6632773
## [686,] -1.946329823 0.4994454
## [687,] -0.051232676 0.5858257
## [688,]  0.885231426 0.6630039
## [689,]  0.883231806 0.6628294
## [690,]  0.909997505 0.6651674
## [691,]  1.274939333 0.6973216
## [692,]  0.269188541 0.6109197
## [693,] -0.002406769 0.5895336
## [694,] -1.376181728 0.5098089
## [695,] -0.738349212 0.5394104
## [696,]  0.405466594 0.6220765
## [697,]  1.616377520 0.7274281
## [698,]  0.246618675 0.6090974
## [699,] -0.069854827 0.5844236
## [700,] -0.616508822 0.5467306
## [701,] -0.263123084 0.5702908
## [702,]  0.540005003 0.6333239
## [703,]  1.285625497 0.6982668
## [704,]  0.732302411 0.6497336
## [705,]  0.598523741 0.6382796
## [706,]  0.445215631 0.6253770
## [707,] -0.263965830 0.5702309
## [708,] -0.566857701 0.5498404
## [709,]  1.616377520 0.7274281
## [710,]  1.616377520 0.7274281
## [711,] -0.430366143 0.5587402
## [712,]  1.616377520 0.7274281
## [713,] -0.227836411 0.5728115
## [714,] -0.592783780 0.5482077
## [715,] -0.633161145 0.5457037
## [716,] -0.404013171 0.5605150
## [717,]  0.056161183 0.5940395
## [718,] -0.267189925 0.5700021
## [719,] -0.301731190 0.5675652
## [720,] -0.512617788 0.5533169
## [721,]  1.303745411 0.6998696
## [722,] -0.325547078 0.5659011
## [723,]  0.046920742 0.5933245
## [724,]  1.101062228 0.6819555
## [725,] -0.376389855 0.5623939
## [726,] -0.206718340 0.5743332
## [727,] -0.771702669 0.5374873
## [728,]  0.677160261 0.6449927
## [729,]  1.616377520 0.7274281
## [730,]  0.318290976 0.6149101
## [731,] -0.051294453 0.5858211
## [732,]  1.360033851 0.7048474
## [733,] -0.675172574 0.5431495
## [734,] -0.875532134 0.5317368
## [735,] -0.384249635 0.5618574
## [736,] -0.200911242 0.5747534
## [737,]  0.287971313 0.6124420
## [738,]  0.245274538 0.6089891
## [739,] -0.965698803 0.5270486
## [740,] -0.352421161 0.5640396
## [741,] -2.119978540 0.4998999
## [742,]  0.623077025 0.6403693
## [743,]  0.502381293 0.6301572
## [744,] -0.779236721 0.5370579
## [745,]  1.082034644 0.6802775
## [746,] -0.018407893 0.5883135
## [747,]  1.616377520 0.7274281
## [748,]  0.968091791 0.6702552
## [749,] -0.027426083 0.5876280
## [750,] -0.834705473 0.5339544
## [751,]  0.979115998 0.6712226
## [752,] -1.431253241 0.5080681
## [753,]  0.432498279 0.6243189
## [754,]  0.704072911 0.6473033
## [755,] -0.265985429 0.5700876
## [756,]  1.303745411 0.6998696
## [757,] -0.589692891 0.5484014
## [758,]  0.279669225 0.6117685
## [759,]  0.518555163 0.6315166
## [760,] -0.193981636 0.5752557
## [761,] -0.429834000 0.5587759
## [762,] -0.032193318 0.5872662
## [763,] -1.373028766 0.5099130
## [764,]  0.218878658 0.6068680
## [765,] -0.514532644 0.5531928
## [766,]  1.173672145 0.6883669
## [767,] -0.155837297 0.5780391
## [768,] -0.480767127 0.5553958
## [769,]  0.246070527 0.6090532
## [770,]  0.103058885 0.5976915
## [771,]  0.173544799 0.6032504
## [772,]  1.162996760 0.6874236
## [773,]  0.559254063 0.6349500
## [774,] -0.321802232 0.5661619
## [775,] -0.124430951 0.5803537
## [776,] -0.398145760 0.5609125
## [777,]  1.406647334 0.7089668
## [778,] -0.350841639 0.5641485
## [779,] -0.530071970 0.5521893
## [780,]  0.736533966 0.6500985
## [781,]  1.109447016 0.6826952
## [782,]  1.232872456 0.6936008
## [783,] -0.393781589 0.5612087
## [784,] -0.519141407 0.5528945
## [785,] -0.861150664 0.5325114
## [786,] -0.631219856 0.5458230
## [787,]  0.951789958 0.6688258
## [788,]  1.616377520 0.7274281
## [789,] -0.230328850 0.5726325
## [790,] -0.446861179 0.5576384
## [791,] -0.050955167 0.5858467
## [792,]  1.232872456 0.6936008
## [793,]  0.687046510 0.6458408
## [794,]  1.616377520 0.7274281
## [795,]  0.974080250 0.6707806
## [796,]  0.990896121 0.6722569
## [797,]  0.754492831 0.6516486
## [798,]  0.174971775 0.6033638
## [799,] -0.663804663 0.5438354
## [800,]  0.492316373 0.6293128
## [801,] -0.474332244 0.5558191
## [802,]  1.083597832 0.6804153
## [803,] -0.099009072 0.5822421
## [804,] -0.252499438 0.5710468
## [805,]  1.066214396 0.6788831
## [806,]  0.784029610 0.6542035
## [807,]  0.791985376 0.6548927
## [808,] -0.443115177 0.5578880
## [809,] -2.099422643 0.4997542
## [810,] -0.045644507 0.5862478
## [811,] -0.292429656 0.5682187
## [812,]  0.161178818 0.6022692
## [813,]  0.161865468 0.6023237
## [814,]  0.745556958 0.6508770
## [815,] -0.603605244 0.5475320
## [816,] -0.037280524 0.5868806
## [817,]  0.197853367 0.6051862
## [818,] -0.053585304 0.5856482
## [819,] -0.336177285 0.5651627
## [820,] -1.135954714 0.5190365
## [821,]  0.540005003 0.6333239
## [822,]  0.116760911 0.5987657
## [823,] -0.587395578 0.5485455
## [824,]  1.616377520 0.7274281
## [825,]  0.224480426 0.6073173
## [826,]  0.158151677 0.6020294
## [827,] -0.303838061 0.5674175
## [828,]  0.439276053 0.6248826
## [829,]  0.719596892 0.6486390
## [830,] -0.503683094 0.5538973
## [831,] -0.841832944 0.5335631
## [832,]  1.013933960 0.6742814
## [833,]  1.616377520 0.7274281
## [834,]  1.399015062 0.7082925
## [835,]  1.274939333 0.6973216
## [836,]  1.616377520 0.7274281
## [837,]  0.995545555 0.6726653
## [838,]  0.532788226 0.6327152
## [839,]  0.193247155 0.6048187
## [840,] -0.248758337 0.5713136
## [841,]  1.082034644 0.6802775
## [842,] -0.160574924 0.5776917
## [843,]  0.300134110 0.6134305
## [844,]  0.795368123 0.6551860
## [845,] -0.798445198 0.5359715
## [846,]  1.406647334 0.7089668
## [847,]  1.616377520 0.7274281
## [848,] -0.265030911 0.5701553
## [849,] -0.198145257 0.5749538
## [850,] -0.627273551 0.5460659
## [851,]  0.300401547 0.6134523
## [852,] -0.661111682 0.5439985
## [853,] -0.669568014 0.5434872
## [854,] -0.001708115 0.5895870
## [855,] -0.349991494 0.5642071
## [856,] -0.168436523 0.5771163
## [857,] -0.527204517 0.5523740
## [858,] -0.877946671 0.5316075
## [859,]  0.236865920 0.6083123
## [860,] -1.318688225 0.5117803
## [861,]  0.587105441 0.6373098
## [862,] -0.335728976 0.5651938
## [863,]  0.440628647 0.6249951
## [864,]  0.174737757 0.6033452
## [865,]  0.554735708 0.6345680
## [866,] -0.685824173 0.5425105
## [867,] -0.764621227 0.5378926
## [868,]  0.548567879 0.6340468
## [869,]  1.406647334 0.7089668
## [870,] -1.695905298 0.5018396
## [871,]  0.593719446 0.6378714
## [872,]  0.290849820 0.6126758
## [873,]  1.307713279 0.7002206
## [874,]  0.110673096 0.5982880
## [875,] -0.478337828 0.5555555
## [876,]  0.439717092 0.6249192
## [877,]  1.303745411 0.6998696
## [878,] -0.362431553 0.5633506
## [879,] -0.545576210 0.5511947
## [880,]  0.049491406 0.5935232
## [881,]  0.686301489 0.6457769
## [882,]  0.384831126 0.6203710
## [883,]  0.118685237 0.5989168
## [884,]  1.173672145 0.6883669
## [885,] -0.031782803 0.5872973
## [886,]  0.625592391 0.6405837
## [887,]  0.854716910 0.6603433
## [888,] -0.348749406 0.5642929
## [889,]  0.625592391 0.6405837
## [890,] -0.268615977 0.5699009
## [891,]  0.917692056 0.6658403
## [892,] -0.166055695 0.5772905
## [893,]  0.867245008 0.6614350
## [894,]  0.283746875 0.6120992
## [895,] -0.533830797 0.5519476
## [896,]  1.616377520 0.7274281
## [897,]  0.199879431 0.6053480
## [898,]  0.056554595 0.5940700
## [899,]  0.295271177 0.6130351
## [900,]  1.162996760 0.6874236
## [901,] -0.974051958 0.5266293
## [902,]  0.131947218 0.5999598
## [903,] -0.770786871 0.5375396
## [904,]  0.847938099 0.6597531
## [905,]  0.728930190 0.6494430
## [906,] -2.213112331 0.5008704
## [907,]  0.337831652 0.6165075
## [908,] -0.100494139 0.5821314
## [909,] -0.119981080 0.5806833
## [910,]  0.722436894 0.6488835
## [911,]  1.075007290 0.6796580
## [912,] -0.399594395 0.5608143
## [913,]  0.791985376 0.6548927
## [914,] -0.550547554 0.5508772
## [915,] -0.000290885 0.5896953
## 
## $scores$noDIF_conservative
##                   F1     SE_F1
##   [1,] -0.3038239606 0.5531481
##   [2,] -1.4032538443 0.4956733
##   [3,] -0.5038713617 0.5397761
##   [4,]  0.1723240678 0.5887213
##   [5,]  0.4890588878 0.6147293
##   [6,] -0.2404759056 0.5575934
##   [7,]  0.9604925031 0.6558389
##   [8,]  0.7803118949 0.6398643
##   [9,] -1.3372966608 0.4978182
##  [10,] -0.2127895394 0.5595663
##  [11,] -1.3901213766 0.4960843
##  [12,] -0.7287094618 0.5260831
##  [13,] -1.7743846504 0.4875754
##  [14,] -1.4634843568 0.4938926
##  [15,]  0.1785875450 0.5892195
##  [16,] -0.3010960305 0.5533375
##  [17,] -0.3810872446 0.5478601
##  [18,] -0.5570192668 0.5364050
##  [19,] -0.5415121049 0.5373803
##  [20,] -0.6216039722 0.5324179
##  [21,]  0.9349794124 0.6535616
##  [22,] -0.7562101282 0.5245147
##  [23,]  0.1637489176 0.5880403
##  [24,] -0.4934459066 0.5404466
##  [25,] -1.9275623674 0.4863404
##  [26,]  1.2240929276 0.6795758
##  [27,] -0.0130123290 0.5743108
##  [28,] -0.7085124670 0.5272504
##  [29,]  0.1206013784 0.5846340
##  [30,] -0.6231618038 0.5323233
##  [31,]  0.0057566309 0.5757396
##  [32,] -1.0851837220 0.5077808
##  [33,] -1.1840220722 0.5035546
##  [34,]  0.7539795570 0.6375534
##  [35,] -1.2247180210 0.5019321
##  [36,]  0.1937026721 0.5904248
##  [37,]  1.3512034830 0.6911023
##  [38,] -0.2721049954 0.5553618
##  [39,] -0.5469987641 0.5370344
##  [40,]  0.9351952667 0.6535809
##  [41,] -0.8055210954 0.5217643
##  [42,]  0.5957631552 0.6238217
##  [43,]  0.8897795542 0.6495386
##  [44,]  0.7578066662 0.6378888
##  [45,] -0.2982307379 0.5535367
##  [46,] -0.6201954969 0.5325035
##  [47,] -0.0233601432 0.5735261
##  [48,]  1.4808958937 0.7028702
##  [49,] -0.3684751603 0.5487129
##  [50,]  0.1553211899 0.5873723
##  [51,]  1.6715601293 0.7201100
##  [52,] -1.3152719052 0.4985788
##  [53,] -0.7348940967 0.5257283
##  [54,] -0.0862084072 0.5688081
##  [55,] -0.3848396001 0.5476071
##  [56,] -1.2494162031 0.5009819
##  [57,]  0.0430812162 0.5786021
##  [58,]  1.1828278447 0.6758409
##  [59,] -0.1424752209 0.5646560
##  [60,] -1.8280555203 0.4869970
##  [61,] -0.4282383272 0.5447081
##  [62,]  0.1512513950 0.5870502
##  [63,]  0.1507665430 0.5870118
##  [64,] -1.1305623603 0.5057911
##  [65,] -0.2412433295 0.5575390
##  [66,] -0.8885529419 0.5173182
##  [67,]  0.1108799287 0.5838713
##  [68,] -1.5601332662 0.4914024
##  [69,]  0.0340082932 0.5779038
##  [70,]  1.3348304315 0.6896165
##  [71,] -0.3586723080 0.5493787
##  [72,] -0.2448321493 0.5572847
##  [73,] -0.2682455963 0.5556328
##  [74,]  0.0365654966 0.5781004
##  [75,]  0.8602413468 0.6469181
##  [76,] -0.1438631962 0.5645544
##  [77,]  0.1287631874 0.5852757
##  [78,] -1.0837953871 0.5078430
##  [79,]  1.6715601293 0.7201100
##  [80,]  0.7665367327 0.6386546
##  [81,]  0.4062219334 0.6077772
##  [82,]  0.2575624543 0.5955610
##  [83,] -1.0109482086 0.5112108
##  [84,] -0.2511861596 0.5568351
##  [85,]  0.5979417627 0.6240089
##  [86,]  0.0142182841 0.5763861
##  [87,] -1.2680375688 0.5002830
##  [88,]  0.7059104008 0.6333526
##  [89,] -0.5298990058 0.5381152
##  [90,] -0.0153820324 0.5741309
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## [512,]  0.1037052562 0.5833096
## [513,]  0.1779340905 0.5891675
## [514,] -0.7341528929 0.5257707
## [515,] -0.0042393877 0.5749778
## [516,]  1.0924454530 0.6676809
## [517,] -0.9966120300 0.5118976
## [518,] -0.2473670703 0.5571052
## [519,]  0.7664809785 0.6386497
## [520,]  0.2238003522 0.5928368
## [521,] -0.1868926338 0.5614277
## [522,] -0.2385796842 0.5577280
## [523,]  1.1598097493 0.6737599
## [524,]  1.0263177619 0.6617340
## [525,]  0.2793598097 0.5973300
## [526,] -0.0704372185 0.5699843
## [527,] -0.0985577199 0.5678909
## [528,]  0.3880341322 0.6062641
## [529,] -1.6044709917 0.4904157
## [530,]  1.1828278447 0.6758409
## [531,] -0.0504525379 0.5714822
## [532,]  0.5779452554 0.6222933
## [533,] -1.5387175438 0.4919144
## [534,] -0.9660984085 0.5133850
## [535,] -0.8309145806 0.5203795
## [536,]  0.9630991407 0.6560718
## [537,] -0.4329235542 0.5443981
## [538,] -0.3394923940 0.5506882
## [539,]  0.5191570635 0.6172790
## [540,] -0.2820096183 0.5546679
## [541,]  0.8897795542 0.6495386
## [542,] -0.0412957002 0.5721713
## [543,]  0.8572516223 0.6466532
## [544,] -0.0061472468 0.5748326
## [545,]  0.9813469438 0.6577036
## [546,]  0.9535305655 0.6552170
## [547,]  0.5102970558 0.6165272
## [548,]  1.4808958937 0.7028702
## [549,] -0.5676781156 0.5357386
## [550,] -0.3029959725 0.5532055
## [551,] -0.1239445612 0.5660158
## [552,]  0.2275787326 0.5931407
## [553,]  0.3509133861 0.6031916
## [554,] -1.1523671261 0.5048646
## [555,]  0.7602383323 0.6381020
## [556,]  1.3348304315 0.6896165
## [557,]  0.3349387872 0.6018759
## [558,]  0.1598228811 0.5877289
## [559,]  0.0958772777 0.5826978
## [560,] -0.9348922143 0.5149417
## [561,]  1.4808958937 0.7028702
## [562,] -0.0695054342 0.5700539
## [563,] -0.5814736457 0.5348810
## [564,]  0.2095285031 0.5916911
## [565,] -0.5514532456 0.5367543
## [566,]  0.5480969530 0.6197419
## [567,] -0.7389098458 0.5254985
## [568,]  0.6145723305 0.6254393
## [569,] -0.6680437241 0.5296278
## [570,]  0.7952865872 0.6411815
## [571,]  0.2380852504 0.5939870
## [572,] -0.0007918744 0.5752403
## [573,]  0.3263368429 0.6011690
## [574,] -0.4360567575 0.5441911
## [575,] -0.8190801078 0.5210221
## [576,]  0.4527656500 0.6116714
## [577,] -0.4598624646 0.5426270
## [578,] -0.1015697709 0.5676677
## [579,]  0.3310814547 0.6015588
## [580,] -0.4521662056 0.5431310
## [581,]  0.5295604432 0.6181631
## [582,]  0.5460602537 0.6195682
## [583,]  0.0744710873 0.5810307
## [584,] -0.1937651425 0.5609322
## [585,] -0.7872883079 0.5227719
## [586,] -1.0477766336 0.5094825
## [587,] -0.9768822042 0.5128554
## [588,]  0.2721333206 0.5967426
## [589,] -0.7619226473 0.5241920
## [590,]  0.0440521779 0.5786770
## [591,] -0.3149090588 0.5523802
## [592,] -1.0302130676 0.5103003
## [593,]  0.0414355216 0.5784753
## [594,]  0.1592906881 0.5876868
## [595,]  1.0924454530 0.6676809
## [596,] -0.9925969740 0.5120913
## [597,] -2.0410857671 0.4862608
## [598,] -0.8025213209 0.5219293
## [599,] -0.0642477538 0.5704473
## [600,]  0.4726528042 0.6133447
## [601,]  0.8019532290 0.6417685
## [602,]  0.3656166173 0.6044061
## [603,] -0.0658302708 0.5703288
## [604,] -0.9615035328 0.5136119
## [605,] -0.1066443932 0.5672921
## [606,]  0.6977735120 0.6326439
## [607,] -0.9247742181 0.5154540
## [608,]  0.4314721122 0.6098859
## [609,]  1.3348304315 0.6896165
## [610,] -0.6901866648 0.5283206
## [611,]  0.4286950994 0.6096536
## [612,]  0.2913021692 0.5983025
## [613,] -0.0928614232 0.5683136
## [614,] -0.5762434477 0.5352055
## [615,] -0.0228156015 0.5735674
## [616,] -1.1882887457 0.5033812
## [617,]  0.2035184111 0.5912097
## [618,] -0.0381702194 0.5724069
## [619,]  1.0674324441 0.6654289
## [620,]  0.5773958111 0.6222463
## [621,]  0.5872379598 0.6230899
## [622,]  0.5562842092 0.6204406
## [623,] -0.3480828839 0.5501005
## [624,] -0.6205072406 0.5324846
## [625,] -0.3325867680 0.5511620
## [626,]  0.2830708678 0.5976320
## [627,] -0.2172148547 0.5592497
## [628,] -0.6375743868 0.5314510
## [629,] -0.5387569980 0.5375543
## [630,]  0.8251337025 0.6438129
## [631,] -0.1373853635 0.5650287
## [632,] -0.0530872937 0.5712842
## [633,] -0.6612374427 0.5300326
## [634,] -1.3775012442 0.4964868
## [635,] -0.4032959411 0.5463682
## [636,]  0.8635837270 0.6472143
## [637,] -1.4341754234 0.4947376
## [638,] -1.5098786899 0.4926399
## [639,] -0.6255654919 0.5321774
## [640,] -0.1666232928 0.5628954
## [641,]  1.6715601293 0.7201100
## [642,] -1.3714371777 0.4966829
## [643,]  0.4009108826 0.6073349
## [644,]  1.4703910725 0.7019176
## [645,] -0.1865151234 0.5614550
## [646,]  0.1732342482 0.5887936
## [647,] -0.7137382017 0.5269471
## [648,] -1.0612823483 0.5088618
## [649,]  0.2026082772 0.5911368
## [650,] -0.3951284899 0.5469154
## [651,] -0.3710207154 0.5485405
## [652,] -1.0887197866 0.5076228
## [653,]  0.9535305655 0.6552170
## [654,]  1.6715601293 0.7201100
## [655,]  1.2240929276 0.6795758
## [656,]  0.5760347120 0.6221297
## [657,] -1.8586672379 0.4867372
## [658,]  0.9494974008 0.6548569
## [659,] -1.2907509133 0.4994511
## [660,]  0.7256207844 0.6350723
## [661,]  0.5522846608 0.6200992
## [662,]  0.9234544205 0.6525344
## [663,] -0.0158043033 0.5740989
## [664,] -0.8792832689 0.5178027
## [665,]  0.6186389289 0.6257896
## [666,] -0.0600416671 0.5707624
## [667,]  0.8507904967 0.6460812
## [668,] -0.6935483532 0.5281235
## [669,]  0.4601756051 0.6122942
## [670,]  1.4428250503 0.6994171
## [671,] -1.4689469135 0.4937397
## [672,]  0.7986798917 0.6414802
## [673,]  0.8185773726 0.6432342
## [674,] -1.8686651020 0.4866634
## [675,]  0.1649777366 0.5881378
## [676,] -0.5489814932 0.5369097
## [677,] -0.7721475963 0.5236170
## [678,]  0.4857633418 0.6144509
## [679,] -0.1074617066 0.5672317
## [680,] -1.1409669005 0.5053466
## [681,]  0.0427514134 0.5785767
## [682,] -0.7290553696 0.5260632
## [683,]  0.7664809785 0.6386497
## [684,]  0.7492622992 0.6371401
## [685,]  0.9440987735 0.6543751
## [686,] -1.8044803567 0.4872319
## [687,] -0.1761618856 0.5622036
## [688,]  0.6446412257 0.6280340
## [689,]  0.9680810154 0.6565171
## [690,]  0.9800318772 0.6575860
## [691,]  1.0412537835 0.6630752
## [692,]  0.3616748623 0.6040801
## [693,]  0.0940641281 0.5825562
## [694,] -1.4385962617 0.4946075
## [695,] -0.6268726650 0.5320981
## [696,]  0.4926146552 0.6150299
## [697,]  1.6715601293 0.7201100
## [698,]  0.3408260456 0.6023603
## [699,] -0.2025562816 0.5603000
## [700,] -0.5355569512 0.5377567
## [701,] -0.3822886765 0.5477790
## [702,]  0.6107353955 0.6251090
## [703,]  1.3512034830 0.6911023
## [704,]  0.7995863869 0.6415601
## [705,]  0.4393531360 0.6105460
## [706,]  0.2674849864 0.5963653
## [707,] -0.1631784436 0.5631457
## [708,] -0.6669296063 0.5296939
## [709,]  1.6715601293 0.7201100
## [710,]  1.6715601293 0.7201100
## [711,] -0.3347271027 0.5510150
## [712,]  1.3271334049 0.6889180
## [713,] -0.3398514403 0.5506636
## [714,] -0.7160170469 0.5268151
## [715,] -0.7216447719 0.5264899
## [716,] -0.5191480338 0.5387990
## [717,]  0.1524751842 0.5871470
## [718,] -0.1581886365 0.5635088
## [719,] -0.4197788081 0.5452693
## [720,] -0.4049904105 0.5462549
## [721,]  1.3639252904 0.6922569
## [722,] -0.4378795437 0.5440708
## [723,] -0.1210493820 0.5662289
## [724,]  1.1660635086 0.6743251
## [725,] -0.2800493880 0.5548051
## [726,] -0.3290104483 0.5514078
## [727,] -0.8637387192 0.5186220
## [728,]  0.4806717123 0.6140210
## [729,]  1.6715601293 0.7201100
## [730,]  0.4241249445 0.6092714
## [731,] -0.1999566959 0.5604868
## [732,]  1.4231707262 0.6976337
## [733,] -0.5713880572 0.5355074
## [734,] -0.7589661338 0.5243589
## [735,] -0.5065648523 0.5396033
## [736,] -0.0918152737 0.5683913
## [737,]  0.1187887707 0.5844917
## [738,]  0.3274099324 0.6012572
## [739,] -0.8649883226 0.5185558
## [740,] -0.2547636410 0.5565824
## [741,] -2.2849635212 0.4885314
## [742,]  0.7066416264 0.6334164
## [743,]  0.5722815375 0.6218083
## [744,] -0.8487247328 0.5194213
## [745,]  1.1598097493 0.6737599
## [746,]  0.0773935628 0.5812578
## [747,]  1.6715601293 0.7201100
## [748,]  1.0387464267 0.6628500
## [749,] -0.1633818128 0.5631309
## [750,] -0.7291032822 0.5260605
## [751,]  0.7390579835 0.6362469
## [752,] -1.3034607171 0.4989956
## [753,]  0.4889354597 0.6147189
## [754,]  0.7788393119 0.6397349
## [755,] -0.4002705933 0.5465707
## [756,]  1.3639252904 0.6922569
## [757,] -0.4809661146 0.5412533
## [758,]  0.3697811570 0.6047507
## [759,]  0.5858177871 0.6229681
## [760,] -0.3196454526 0.5520531
## [761,] -0.7187621874 0.5266564
## [762,]  0.0713726067 0.5807901
## [763,] -1.2526247647 0.5008604
## [764,]  0.0720076081 0.5808394
## [765,] -0.5939783711 0.5341084
## [766,]  1.2240929276 0.6795758
## [767,] -0.0599432036 0.5707698
## [768,] -0.3742854937 0.5483195
## [769,]  0.3072221332 0.5996026
## [770,]  0.1940166322 0.5904499
## [771,]  0.2570349778 0.5955183
## [772,]  1.2441086323 0.6813890
## [773,]  0.6219355841 0.6260737
## [774,] -0.4490273536 0.5433370
## [775,] -0.2307991230 0.5582809
## [776,] -0.5003201662 0.5400042
## [777,]  1.4808958937 0.7028702
## [778,] -0.2511861596 0.5568351
## [779,] -0.4236277851 0.5450137
## [780,]  0.8271415022 0.6439902
## [781,]  1.1875791693 0.6762707
## [782,]  1.3068669338 0.6870793
## [783,] -0.3027437817 0.5532231
## [784,] -0.6156247405 0.5327819
## [785,] -0.9263656732 0.5153732
## [786,] -0.5271374063 0.5382905
## [787,]  1.0217684208 0.6613257
## [788,]  1.3519745526 0.6911723
## [789,] -0.1371880440 0.5650432
## [790,] -0.3537896095 0.5497112
## [791,]  0.0380778025 0.5782168
## [792,]  1.3068669338 0.6870793
## [793,]  0.4857633418 0.6144509
## [794,]  1.6715601293 0.7201100
## [795,]  1.0384178005 0.6628205
## [796,]  1.0476703638 0.6636518
## [797,]  0.8190718106 0.6432778
## [798,]  0.2830708678 0.5976320
## [799,] -0.5469758527 0.5370359
## [800,]  0.5533869746 0.6201932
## [801,] -0.5988821265 0.5338067
## [802,]  1.1447500576 0.6723993
## [803,] -0.0258358183 0.5733387
## [804,] -0.3910091603 0.5471920
## [805,]  1.1341241089 0.6714398
## [806,]  0.8502564765 0.6460339
## [807,]  0.8785778656 0.6485440
## [808,] -0.5512461534 0.5367673
## [809,] -1.9554857019 0.4862543
## [810,] -0.1940729323 0.5609101
## [811,] -0.2020708986 0.5603349
## [812,]  0.2439173939 0.5944576
## [813,]  0.2274383556 0.5931294
## [814,]  0.5615167677 0.6208876
## [815,] -0.7143107173 0.5269139
## [816,]  0.0559656551 0.5795966
## [817,]  0.2506384240 0.5950007
## [818,]  0.0344766566 0.5779398
## [819,] -0.4701148774 0.5419581
## [820,] -1.1946282419 0.5031250
## [821,]  0.3490986843 0.6030419
## [822,]  0.1686108111 0.5884262
## [823,] -0.4754634158 0.5416103
## [824,]  1.6715601293 0.7201100
## [825,]  0.3216193486 0.6007819
## [826,] -0.0021272001 0.5751386
## [827,] -0.4249838657 0.5449238
## [828,]  0.5150073368 0.6169267
## [829,]  0.5269435659 0.6179406
## [830,] -0.3899986006 0.5472599
## [831,] -0.9112527008 0.5161444
## [832,]  1.0927209848 0.6677058
## [833,]  1.6715601293 0.7201100
## [834,]  1.4703910725 0.7019176
## [835,]  1.0183874537 0.6610224
## [836,]  1.6715601293 0.7201100
## [837,]  0.7849112442 0.6402687
## [838,]  0.5923456225 0.6235283
## [839,]  0.2779071403 0.5972119
## [840,] -0.3802434478 0.5479170
## [841,]  1.1598097493 0.6737599
## [842,] -0.2989727947 0.5534851
## [843,]  0.4062219334 0.6077772
## [844,]  0.6161668004 0.6255766
## [845,] -1.0464675543 0.5095430
## [846,]  1.4808958937 0.7028702
## [847,]  1.6715601293 0.7201100
## [848,] -0.4097983128 0.5459339
## [849,] -0.3048080622 0.5530798
## [850,] -0.7362043745 0.5256533
## [851,]  0.3688451172 0.6046732
## [852,] -0.5648312677 0.5359163
## [853,] -0.5707563617 0.5355467
## [854,]  0.0743945199 0.5810247
## [855,] -0.2596008798 0.5562412
## [856,] -0.3117581966 0.5525982
## [857,] -0.4451711038 0.5435905
## [858,] -0.9629005817 0.5135429
## [859,]  0.3402019952 0.6023089
## [860,] -1.1831257569 0.5035911
## [861,]  0.6648121012 0.6297804
## [862,] -0.2381602845 0.5577578
## [863,]  0.2324338148 0.5935315
## [864,]  0.2643314436 0.5961095
## [865,]  0.6204248644 0.6259435
## [866,] -0.7549292123 0.5245872
## [867,] -0.8415254737 0.5198073
## [868,]  0.6223926701 0.6261131
## [869,]  1.4808958937 0.7028702
## [870,] -1.5579153495 0.4914544
## [871,]  0.6592364210 0.6292972
## [872,]  0.3760115030 0.6052667
## [873,]  1.3589467658 0.6918051
## [874,]  0.2006545447 0.5909805
## [875,] -0.3651071419 0.5489414
## [876,]  0.5363317504 0.6187393
## [877,]  1.3639252904 0.6922569
## [878,] -0.4754456257 0.5416115
## [879,] -0.6491462741 0.5307552
## [880,]  0.1311510553 0.5854637
## [881,]  0.7663040587 0.6386342
## [882,]  0.4610014805 0.6123637
## [883,]  0.2161642793 0.5922233
## [884,]  1.2240929276 0.6795758
## [885,] -0.1714825076 0.5625427
## [886,]  0.4360561904 0.6102698
## [887,]  0.9328213159 0.6533692
## [888,] -0.2344412109 0.5580219
## [889,]  0.4360561904 0.6102698
## [890,] -0.3971638335 0.5467789
## [891,]  1.0098808776 0.6602595
## [892,] -0.0504525379 0.5714822
## [893,]  0.9234544205 0.6525344
## [894,]  0.3743915393 0.6051325
## [895,] -0.4282383272 0.5447081
## [896,]  1.6715601293 0.7201100
## [897,]  0.0571114789 0.5796852
## [898,]  0.1507665430 0.5870118
## [899,]  0.3962643625 0.6069482
## [900,]  1.2441086323 0.6813890
## [901,] -1.0367574551 0.5099942
## [902,] -0.0232867397 0.5735317
## [903,] -0.8636190758 0.5186283
## [904,]  0.9089134862 0.6512398
## [905,]  0.8076268680 0.6422685
## [906,] -2.0844939009 0.4864208
## [907,]  0.1677068685 0.5883544
## [908,] -0.2225146569 0.5588713
## [909,] -0.0418706500 0.5721280
## [910,]  0.5319345889 0.6183651
## [911,]  1.1501564652 0.6728876
## [912,] -0.4929853109 0.5404763
## [913,]  0.8785778656 0.6485440
## [914,] -0.4427648829 0.5437488
## [915,]  0.0995441598 0.5829842
## 
## $scores$anchor_liberal
##               F1     SE_F1
## 1    0.422353318 0.7099637
## 2   -0.999256494 0.6378612
## 3    0.177917931 0.6939131
## 4    1.061000808 0.7571531
## 5    1.463724621 0.7900813
## 6    0.511261374 0.7161007
## 7    2.063119206 0.8421707
## 8    1.839187198 0.8223982
## 9   -0.864181624 0.6421472
## 10   0.586801685 0.7214329
## 11  -0.940657936 0.6396414
## 12  -0.100382377 0.6772448
## 13  -1.427703141 0.6287773
## 14  -1.091301825 0.6353167
## 15   1.055268590 0.7567001
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## 525  1.191277715 0.7675737
## 526  0.735659869 0.7322431
## 527  0.697992708 0.7294708
## 528  1.330087425 0.7789273
## 529 -1.217351545 0.6323473
## 530  2.353914539 0.8680193
## 531  0.763547481 0.7343113
## 532  1.564371439 0.7986133
## 533 -1.181153214 0.6331379
## 534 -1.259008210 0.3274646
## 535 -0.227225988 0.6702714
## 536  2.050646866 0.8410634
## 537  0.292736979 0.7012976
## 538  0.380052983 0.7070982
## 539  1.501642020 0.7932830
## 540  0.493920264 0.7148917
## 541  1.972928484 0.8341769
## 542  0.772188377 0.7349548
## 543  1.930150966 0.8303982
## 544  0.819936166 0.7385331
## 545  2.091387545 0.8446820
## 546  2.045984842 0.8406497
## 547  1.489101501 0.7922223
## 548  2.733557115 0.9008017
## 549  0.105899953 0.6894281
## 550  0.428235430 0.7103649
## 551  0.661376412 0.7267995
## 552  1.110818300 0.7611098
## 553  1.310017713 0.7772706
## 554 -0.687583613 0.6486922
## 555  1.842632531 0.8227002
## 556  2.547476876 0.8850065
## 557  1.257665306 0.7729728
## 558  1.032094281 0.7548737
## 559  0.952421841 0.7486554
## 560 -0.355127299 0.6636674
## 561  2.733557115 0.9008017
## 562  0.727107204 0.7316115
## 563  0.093026536 0.6886387
## 564  1.091952731 0.7596073
## 565  0.105231950 0.6893871
## 566  1.527995999 0.7955173
## 567 -0.130575149 0.6755479
## 568  1.624026396 0.8037192
## 569 -0.031619038 0.6811934
## 570  1.842592147 0.8226967
## 571  1.134797175 0.7630269
## 572  0.825657662 0.7389645
## 573  1.247892922 0.7721744
## 574  0.260494834 0.6991956
## 575 -0.237477762 0.6697259
## 576  1.415238126 0.7860104
## 577  0.232567157 0.6973927
## 578  0.697946430 0.7294674
## 579  1.250185339 0.7723616
## 580  0.231644417 0.6973334
## 581  1.500412616 0.7931789
## 582  1.525113510 0.7952726
## 583  0.919346789 0.7461024
## 584  0.569635089 0.7202118
## 585 -0.188141977 0.6723762
## 586 -0.518877215 0.6558791
## 587 -0.399983462 0.6614576
## 588  1.173737992 0.7661571
## 589 -0.152434245 0.6743336
## 590  0.879272372 0.7430320
## 591  0.427839825 0.7103379
## 592 -0.503340144 0.6565846
## 593  0.879413344 0.7430428
## 594  1.038475176 0.7553758
## 595  2.231589176 0.8571551
## 596 -0.467170447 0.6582547
## 597 -1.351695880 0.3674758
## 598 -0.198023437 0.6718403
## 599  0.724484758 0.7314181
## 600  1.426226363 0.7869306
## 601  1.859001501 0.8241363
## 602  1.335141883 0.7793453
## 603  0.734588843 0.7321640
## 604 -0.398128328 0.6615479
## 605  0.735109953 0.7322025
## 606  1.715782409 0.8116378
## 607 -0.365396527 0.6631566
## 608  1.377735149 0.7828802
## 609  2.547476876 0.8850065
## 610 -0.062471300 0.6794075
## 611  1.375900229 0.7827275
## 612  1.206513630 0.7688077
## 613  0.709547082 0.7303186
## 614  0.075198068 0.6875516
## 615  0.789556463 0.7362520
## 616 -0.696140799 0.6483514
## 617  1.091383998 0.7595621
## 618  0.764351468 0.7343711
## 619  2.205218098 0.8548085
## 620  1.569265949 0.7990309
## 621  1.577965962 0.7997738
## 622  1.541278041 0.7966462
## 623  0.388458641 0.7076647
## 624  0.036667203 0.6852273
## 625  0.397198124 0.7082553
## 626  1.192050829 0.7676363
## 627  0.543999110 0.7183985
## 628  0.005292214 0.6833601
## 629  0.126572420 0.6907037
## 630  1.883720287 0.8263083
## 631  0.650997774 0.7260467
## 632  0.755933740 0.7337454
## 633 -0.007153992 0.6826259
## 634 -0.921873337 0.6402379
## 635  0.294059352 0.7013843
## 636  1.966173204 0.8335796
## 637 -1.022614736 0.6371861
## 638 -1.100998083 0.6350669
## 639  0.025050920 0.6845333
## 640  0.611289388 0.7231840
## 641  2.977374104 0.9199211
## 642 -0.935933446 0.6397903
## 643  1.346699301 0.7803023
## 644  2.716577441 0.8993933
## 645  0.582362644 0.7211166
## 646  1.049388042 0.7562359
## 647 -0.089695357 0.6778509
## 648 -0.521686726 0.6557523
## 649  1.087540237 0.7592566
## 650  0.313428555 0.7026580
## 651  0.337115224 0.7042262
## 652 -0.577293807 0.6532913
## 653  1.564400436 0.7130914
## 654  2.977374104 0.9199211
## 655  2.405637893 0.8725921
## 656  1.562115084 0.7984208
## 657 -1.585980556 0.6272830
## 658  2.050411070 0.8410425
## 659 -0.813339828 0.6439247
## 660  1.758650611 0.8153623
## 661  1.540445395 0.7965754
## 662  2.019765375 0.8383242
## 663  0.800930250 0.7371043
## 664 -0.297202326 0.6666036
## 665  1.616019251 0.8030319
## 666  0.742528021 0.7327513
## 667  1.925539945 0.8299915
## 668 -0.048146760 0.6802338
## 669  1.419967261 0.7864063
## 670  2.683677206 0.8966427
## 671 -1.061956021 0.6360940
## 672  1.861546907 0.8243598
## 673  1.867916823 0.8249192
## 674 -1.604866915 0.6271749
## 675  1.029185646 0.7546450
## 676  0.187872739 0.5417147
## 677 -0.168675889 0.6734392
## 678  1.447015646 0.7886754
## 679  0.683606106 0.7284185
## 680 -0.605682580 0.6520712
## 681  0.882782878 0.7433000
## 682 -0.102338982 0.6771342
## 683  1.817478294 0.8204969
## 684  1.774020379 0.8167012
## 685  2.047775562 0.8408086
## 686 -1.507757735 0.6278909
## 687  0.600335091 0.7223993
## 688  1.640457247 0.8051316
## 689  2.082353651 0.8438792
## 690  2.091229429 0.8446679
## 691  2.221501543 0.8562575
## 692  1.288053824 0.7754633
## 693  0.949760609 0.7484493
## 694 -1.017056599 0.6373449
## 695  0.013353959 0.6838377
## 696  1.461909565 0.7899284
## 697  2.977374104 0.9199211
## 698  1.276532435 0.7745177
## 699  0.565066576 0.7198878
## 700  0.139037621 0.6914775
## 701  0.336995967 0.7042183
## 702  1.611898851 0.8026784
## 703  2.572341627 0.8871562
## 704  1.863188225 0.8245039
## 705  1.445542672 0.7885516
## 706  1.167454724 0.7656506
## 707  0.611962527 0.7232323
## 708  0.123337884 0.5263716
## 709  2.977374104 0.9199211
## 710  2.977374104 0.9199211
## 711  0.387790431 0.7076196
## 712  2.528556069 0.8833644
## 713  0.380569884 0.7071330
## 714 -0.115274975 0.6764050
## 715 -0.107672330 0.6768330
## 716  0.176785029 0.6938417
## 717  1.020166522 0.7539367
## 718  0.617462333 0.7236272
## 719  0.281744358 0.7005785
## 720  0.318320356 0.7029809
## 721  2.581633879 0.8879570
## 722  0.251002550 0.6985809
## 723  0.668840924 0.7273422
## 724  2.314479080 0.8645226
## 725  0.461661009 0.7126581
## 726  0.401709957 0.7085608
## 727 -0.244407501 0.6693588
## 728  1.439222786 0.7880208
## 729  2.977374104 0.9199211
## 730  1.369723124 0.7822136
## 731  0.561986407 0.7196695
## 732  2.670685705 0.8955492
## 733  0.095710691 0.6888030
## 734 -0.127035393 0.6757456
## 735  0.191740632 0.6947871
## 736  0.710001854 0.7303520
## 737  0.977930340 0.7506359
## 738  1.240871915 0.7716016
## 739 -0.269844085 0.6680220
## 740  0.478175094 0.7137990
## 741 -2.085134667 0.6295944
## 742  1.722977849 0.8122619
## 743  1.572304102 0.7992902
## 744 -0.227923778 0.6702342
## 745  2.322256770 0.8652128
## 746  0.929413961 0.7468776
## 747  2.977374104 0.9199211
## 748  2.162363159 0.8509946
## 749  0.634460422 0.7248510
## 750 -0.118201042 0.6762406
## 751  1.761054447 0.8155716
## 752 -0.856551013 0.6424083
## 753  1.461433076 0.7898883
## 754  1.834619522 0.8219979
## 755  0.310734889 0.7024804
## 756  2.581633879 0.8879570
## 757  0.207195078 0.6957692
## 758  1.305989880 0.7769387
## 759  1.583836184 0.8002755
## 760  0.419060824 0.7097393
## 761 -0.073595261 0.6787693
## 762  0.912558459 0.7455805
## 763 -0.787937728 0.6448456
## 764  0.912177144 0.7455512
## 765  0.094742940 0.6887437
## 766  2.405637893 0.8725921
## 767  0.754578709 0.7336447
## 768  0.344787144 0.7047366
## 769  1.222376003 0.7700956
## 770  1.073888513 0.7581733
## 771  1.166384632 0.7655644
## 772  2.440025376 0.8756212
## 773  1.611970836 0.8026846
## 774  0.243423967 0.6980916
## 775  0.595027131 0.7220199
## 776  0.218107242 0.6964657
## 777  2.733557115 0.9008017
## 778  0.506862076 0.7157934
## 779  0.284980151 0.7007899
## 780  1.888616165 0.8267390
## 781  2.354903252 0.8681068
## 782  2.513317131 0.8820383
## 783  0.431392649 0.7105806
## 784  0.035837556 0.6851776
## 785 -0.365376900 0.6631575
## 786  0.153348588 0.6923701
## 787  2.149468741 0.8498473
## 788  2.624320548 0.8916160
## 789  0.646048612 0.7256883
## 790  0.382645793 0.7072728
## 791  0.876485551 0.7428195
## 792  2.513317131 0.8820383
## 793  1.127964322 0.6759810
## 794  2.977374104 0.9199211
## 795  2.156248742 0.8504505
## 796  2.181179071 0.8526691
## 797  1.892213162 0.8270555
## 798  1.192050829 0.7676363
## 799  0.143085718 0.6917295
## 800  1.543653128 0.7968483
## 801  0.042529484 0.6855787
## 802  2.303041560 0.8635072
## 803  0.799272989 0.7369800
## 804  0.308297223 0.7023198
## 805  2.296521720 0.8629281
## 806  1.925030878 0.8299466
## 807  1.964727472 0.8334518
## 808  0.118389433 0.6901976
## 809 -1.686844025 0.6268817
## 810  0.576363945 0.7206898
## 811  0.581674958 0.7210677
## 812  1.149091162 0.7641735
## 813  1.117447771 0.7616390
## 814  1.548155048 0.7972314
## 815 -0.097573345 0.6774038
## 816  0.921351681 0.7462566
## 817  1.139427671 0.7633980
## 818  0.884511366 0.7434320
## 819  0.218663566 0.6965013
## 820 -0.665739515 0.6495727
## 821  1.269280884 0.7739234
## 822  1.044449568 0.7558465
## 823  0.235350879 0.6975716
## 824  2.977374104 0.9199211
## 825  1.241510655 0.7716537
## 826  0.844570923 0.7403940
## 827  0.274284184 0.7000919
## 828  1.489295176 0.7922387
## 829  1.492625591 0.7925202
## 830  0.328287185 0.7036404
## 831 -0.347169258 0.6640654
## 832  2.224692738 0.8565415
## 833  2.977374104 0.9199211
## 834  2.716577441 0.8993933
## 835  2.133177701 0.8483979
## 836  2.977374104 0.9199211
## 837  1.883261488 0.8262680
## 838  1.577323322 0.7997189
## 839  1.187965832 0.7673059
## 840  0.325647615 0.7034656
## 841  2.322256770 0.8652128
## 842  0.438499749 0.7110668
## 843  1.345471651 0.7802006
## 844  1.659498326 0.8067715
## 845 -0.488218493 0.6572782
## 846  2.733557115 0.9008017
## 847  2.977374104 0.9199211
## 848  0.264005650 0.6994234
## 849  0.430649789 0.7105298
## 850 -0.143988032 0.6748014
## 851  1.306942252 0.7770172
## 852  0.104291988 0.6893293
## 853  0.096856514 0.6888732
## 854  0.919109337 0.7460841
## 855  0.498188296 0.7151887
## 856  0.479124958 0.7138648
## 857  0.258130496 0.6990423
## 858 -0.421887122 0.6603992
## 859  1.261811967 0.7733120
## 860 -0.674989434 0.6491980
## 861  1.691135368 0.8095034
## 862  0.523017718 0.7169235
## 863  1.105494933 0.7606854
## 864  1.163838499 0.7653594
## 865  1.652339787 0.8061546
## 866 -0.092036478 0.6777179
## 867 -0.201030057 0.6716778
## 868  1.634523107 0.8046212
## 869  2.733557115 0.9008017
## 870 -1.133317311 0.6342598
## 871  1.678467350 0.8084084
## 872  1.307890243 0.7770953
## 873  2.580599432 0.8878679
## 874  1.078880253 0.7585691
## 875  0.379755842 0.7070781
## 876  1.510786960 0.7940575
## 877  2.581633879 0.8879570
## 878  0.240958051 0.6979326
## 879 -0.017376937 0.6820256
## 880  1.022599161 0.7541276
## 881  1.816247975 0.8203893
## 882  1.421460902 0.7865314
## 883  1.104702038 0.7606222
## 884  2.405637893 0.8725921
## 885  0.634610739 0.7248619
## 886  1.380589920 0.7831179
## 887  2.041856707 0.8402834
## 888  0.533756273 0.7176774
## 889  1.380589920 0.7831179
## 890  0.311382423 0.7025231
## 891  2.123102163 0.8475017
## 892  0.763547481 0.7343113
## 893  2.019765375 0.8383242
## 894  1.308240108 0.7771241
## 895  0.281498593 0.7005624
## 896  2.977374104 0.9199211
## 897  0.893600656 0.7441269
## 898  1.022469461 0.7541174
## 899  1.345813297 0.7802289
## 900  2.440025376 0.8756212
## 901 -0.491740523 0.6571160
## 902  0.785724640 0.7359654
## 903 -0.271291607 0.6679464
## 904  2.008009166 0.8372823
## 905  1.851944457 0.8235169
## 906 -1.865285397 0.6272438
## 907  1.024635919 0.7542875
## 908  0.574359281 0.7205473
## 909  0.774258543 0.7351092
## 910  1.499357989 0.7930897
## 911  2.306592960 0.8638225
## 912  0.189973068 0.6946751
## 913  1.964727472 0.8334518
## 914  0.281891628 0.7005881
## 915  0.962673139 0.7494501
## 
## $scores$anchor_conservative
##               F1     SE_F1
## 1    0.634242053 0.7318632
## 2   -0.820550484 0.6559954
## 3    0.371049265 0.7143290
## 4    1.279553258 0.7799725
## 5    1.704918501 0.8148735
## 6    0.724556822 0.7381827
## 7    2.313867463 0.8675796
## 8    2.079634636 0.8470903
## 9   -0.715953385 0.6594273
## 10   0.759276368 0.7406509
## 11  -0.785515221 0.6571026
## 12   0.081525822 0.6967156
## 13  -1.300383573 0.6454194
## 14  -0.900423982 0.6536343
## 15   1.275561510 0.7796555
## 16   0.653051458 0.7331671
## 17   0.537623073 0.7252694
## 18   0.311341261 0.7105459
## 19   0.325796948 0.7114549
## 20   0.216267816 0.7046802
## 21   2.278190951 0.8644567
## 22   0.046144316 0.6946948
## 23   1.263626088 0.7787092
## 24   0.396556359 0.7159679
## 25  -1.499785702 0.6437087
## 26   2.663375616 0.8977056
## 27   1.033192538 0.7608335
## 28   0.104716953 0.6980564
## 29   1.209875345 0.7744716
## 30   0.222989646 0.7050884
## 31   1.054583569 0.7624601
## 32  -0.389412005 0.6724642
## 33  -0.520928154 0.6668075
## 34   2.034132841 0.8431277
## 35  -0.580095078 0.6644378
## 36   1.296895939 0.7813519
## 37   2.839006431 0.9120272
## 38   0.692912607 0.7359517
## 39   0.315587777 0.7108124
## 40   2.284761038 0.8650320
## 41  -0.027309422 0.6905968
## 42   1.833264160 0.8257856
## 43   2.229378561 0.8601822
## 44   2.047122841 0.8442579
## 45   0.657251346 0.7334592
## 46   0.222875921 0.7050814
## 47   1.024712016 0.7601906
## 48   3.004928842 0.9245348
## 49   0.564972339 0.7271180
## 50   1.248945673 0.7775479
## 51   3.250988818 0.9401597
## 52  -0.697448770 0.6600736
## 53   0.062477996 0.6956239
## 54   0.920848824 0.7524079
## 55   0.540834624 0.7254858
## 56  -0.606961700 0.6633988
## 57   1.099147868 0.7658709
## 58   2.613284734 0.8934830
## 59   0.853163999 0.7474295
## 60  -1.367514775 0.6446604
## 61   0.481968581 0.7215525
## 62   1.239492630 0.7768016
## 63   1.248766404 0.7775337
## 64  -0.438154392 0.6703063
## 65   0.727930747 0.7384216
## 66  -0.130015107 0.6850947
## 67   1.203617660 0.7739809
## 68  -1.009010661 0.6507978
## 69   1.087167409 0.7649510
## 70   2.811326415 0.9098313
## 71   0.566425562 0.7272166
## 72   0.725696367 0.7382634
## 73   0.694167267 0.7360399
## 74   1.086948250 0.7649342
## 75   2.179386815 0.8558057
## 76   0.853742965 0.7474717
## 77   1.207600011 0.7742931
## 78  -0.388555610 0.6725027
## 79   3.250988818 0.9401597
## 80   2.070379023 0.8462835
## 81   1.586088809 0.8049140
## 82   1.389281429 0.7887668
## 83  -0.286409856 0.6772537
## 84   0.718853979 0.7377793
## 85   1.833405237 0.8257976
## 86   1.061569080 0.7629927
## 87  -0.640281846 0.6621428
## 88   1.976498570 0.8381241
## 89   0.348822555 0.7129119
## 90   1.036994780 0.7611221
## 91  -0.681718321 0.6606321
## 92   0.191682614 0.7031959
## 93   1.093536982 0.7654398
## 94   0.403515621 0.7164174
## 95   0.166935485 0.7017157
## 96   1.396836614 0.7893781
## 97   1.216222905 0.7749699
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## 609  2.811326415 0.9098313
## 610  0.129509830 0.6995037
## 611  1.609501864 0.8068646
## 612  1.434233236 0.7924140
## 613  0.922393251 0.7525224
## 614  0.280794864 0.7086398
## 615  1.006545890 0.7588172
## 616 -0.527090076 0.6665555
## 617  1.314769879 0.7827778
## 618  0.986743442 0.7573259
## 619  2.469062036 0.8811068
## 620  1.819348342 0.8245953
## 621  1.816029976 0.8243117
## 622  1.784389302 0.8216126
## 623  0.594359373 0.7291201
## 624  0.217341291 0.7047453
## 625  0.602339515 0.7296666
## 626  1.425593191 0.7917111
## 627  0.750181532 0.7400023
## 628  0.202737069 0.7038616
## 629  0.330881035 0.7117756
## 630  2.127912078 0.8513044
## 631  0.865886706 0.7483595
## 632  0.979819445 0.7568059
## 633  0.174681198 0.7021775
## 634 -0.774790324 0.6574501
## 635  0.498923444 0.7226784
## 636  2.192273707 0.8569336
## 637 -0.853293779 0.6549998
## 638 -0.956168542 0.6521236
## 639  0.217303747 0.7047430
## 640  0.826818141 0.7455122
## 641  3.250988818 0.9401597
## 642 -0.771257116 0.6575655
## 643  1.567076178 0.8033345
## 644  2.990409606 0.9234922
## 645  0.793281114 0.7430886
## 646  1.287270712 0.7805858
## 647  0.107642750 0.6982264
## 648 -0.348706490 0.6743202
## 649  1.310534247 0.7824395
## 650  0.523306042 0.7243075
## 651  0.550016687 0.7261053
## 652 -0.391648432 0.6723636
## 653  1.440786238 0.7030510
## 654  3.250988818 0.9401597
## 655  2.663375616 0.8977056
## 656  1.809505718 0.8237545
## 657 -1.414261343 0.6442411
## 658  2.305244232 0.8668250
## 659 -0.661263647 0.6613707
## 660  2.012389323 0.8412378
## 661  1.775254402 0.8208349
## 662  2.265698007 0.8633628
## 663  1.016347201 0.7595576
## 664 -0.112245323 0.6860272
## 665  1.860833639 0.8281484
## 666  0.968474159 0.7559555
## 667  2.177485921 0.8556394
## 668  0.123053947 0.6991255
## 669  1.656513304 0.8107988
## 670  2.953731859 0.9208100
## 671 -0.896144390 0.6537550
## 672  2.113407303 0.8500374
## 673  2.129764953 0.8514663
## 674 -1.428810435 0.6441290
## 675  1.271652153 0.7793454
## 676  0.004751952 0.6298244
## 677  0.026723509 0.6935984
## 678  1.677744262 0.8125831
## 679  0.900905532 0.7509332
## 680 -0.470239012 0.6689251
## 681  1.101907807 0.7660831
## 682  0.080398353 0.6966507
## 683  2.059258962 0.8453146
## 684  2.038745918 0.8435290
## 685  2.294198506 0.8658582
## 686 -1.342761471 0.6449188
## 687  0.807480235 0.7441124
## 688  1.883917324 0.8301314
## 689  2.337147939 0.8696159
## 690  2.345599170 0.8703547
## 691  2.421068798 0.8769386
## 692  1.533338944 0.8005417
## 693  1.171382221 0.7714617
## 694 -0.858458586 0.6548463
## 695  0.214277002 0.7045595
## 696  1.703991528 0.8147952
## 697  3.250988818 0.9401597
## 698  1.498613552 0.7976806
## 699  0.769712524 0.7413969
## 700  0.338389152 0.7122503
## 701  0.537263467 0.7252452
## 702  1.853567257 0.8275250
## 703  2.839006431 0.9120272
## 704  2.114254098 0.8501113
## 705  1.632889679 0.8088189
## 706  1.393662228 0.7891211
## 707  0.834938709 0.7461019
## 708 -0.110672165 0.6250736
## 709  3.250988818 0.9401597
## 710  3.250988818 0.9401597
## 711  0.609178651 0.7301359
## 712  2.790187051 0.9081369
## 713  0.593571692 0.7290662
## 714  0.091263375 0.6972770
## 715  0.093519915 0.6974074
## 716  0.354649287 0.7132824
## 717  1.252903213 0.7778607
## 718  0.837658807 0.7462997
## 719  0.487219187 0.7219006
## 720  0.515033009 0.7237535
## 721  2.855236156 0.9133021
## 722  0.458769816 0.7200212
## 723  0.882821199 0.7496016
## 724  2.586605288 0.8912154
## 725  0.673005749 0.7345575
## 726  0.604354022 0.7298047
## 727 -0.089281541 0.6872444
## 728  1.677381358 0.8125525
## 729  3.250988818 0.9401597
## 730  1.610852907 0.8069773
## 731  0.774824779 0.7417630
## 732  2.931824852 0.9191768
## 733  0.291961871 0.7093342
## 734  0.044668976 0.6946112
## 735  0.368060377 0.7141379
## 736  0.931804535 0.7532208
## 737  1.202500036 0.7738933
## 738  1.473585680 0.7956273
## 739 -0.096303562 0.6868707
## 740  0.709221538 0.7370993
## 741 -1.978150560 0.6464330
## 742  1.979207028 0.8383588
## 743  1.806051517 0.8234596
## 744 -0.067500134 0.6884115
## 745  2.582006728 0.8908233
## 746  1.159117569 0.7705071
## 747  3.250988818 0.9401597
## 748  2.426704941 0.8774290
## 749  0.824465414 0.7453415
## 750  0.078830356 0.6965606
## 751  2.010373829 0.8410627
## 752 -0.681880609 0.6606263
## 753  1.691351128 0.8137290
## 754  2.085937125 0.8476399
## 755  0.510269958 0.7234351
## 756  2.855236156 0.9133021
## 757  0.408249113 0.7167237
## 758  1.535158147 0.8006919
## 759  1.820166226 0.8246652
## 760  0.620968833 0.7309470
## 761  0.090330783 0.6972231
## 762  1.145569690 0.7694551
## 763 -0.612550301 0.6631856
## 764  1.134409305 0.7685905
## 765  0.263910975 0.7075949
## 766  2.663375616 0.8977056
## 767  0.968928467 0.7559895
## 768  0.552496712 0.7262730
## 769  1.459993326 0.7945153
## 770  1.305390309 0.7820290
## 771  1.394173038 0.7891625
## 772  2.697591743 0.9005602
## 773  1.870833280 0.8290069
## 774  0.443355760 0.7190096
## 775  0.744016452 0.7395634
## 776  0.386663946 0.7153307
## 777  3.004928842 0.9245348
## 778  0.718853979 0.7377793
## 779  0.483271244 0.7216388
## 780  2.143699118 0.8526842
## 781  2.624109012 0.8943995
## 782  2.779312234 0.9072597
## 783  0.652245125 0.7331111
## 784  0.227360171 0.7053543
## 785 -0.181607721 0.6824346
## 786  0.357516070 0.7134650
## 787  2.402972862 0.8753627
## 788  2.831300301 0.9114186
## 789  0.864662129 0.7482699
## 790  0.584053162 0.7284161
## 791  1.099000742 0.7658595
## 792  2.779312234 0.9072597
## 793  1.021767220 0.6796637
## 794  3.250988818 0.9401597
## 795  2.414465634 0.8763638
## 796  2.432779236 0.8779573
## 797  2.128581976 0.8513629
## 798  1.425593191 0.7917111
## 799  0.325897734 0.7114612
## 800  1.784658867 0.8216355
## 801  0.247607864 0.7065918
## 802  2.566678900 0.8895143
## 803  1.014382476 0.7594090
## 804  0.526345637 0.7245114
## 805  2.555744417 0.8885784
## 806  2.176256234 0.8555318
## 807  2.214982882 0.8589217
## 808  0.310128877 0.7104698
## 809 -1.537503452 0.6435711
## 810  0.787240685 0.7426541
## 811  0.788974820 0.7427788
## 812  1.364020382 0.7867284
## 813  1.348422134 0.7854738
## 814  1.784122592 0.8215898
## 815  0.092966270 0.6973754
## 816  1.133663794 0.7685329
## 817  1.375785829 0.7876768
## 818  1.103733475 0.7662235
## 819  0.423518126 0.7177149
## 820 -0.538297395 0.6661003
## 821  1.498181312 0.7976451
## 822  1.274365063 0.7795606
## 823  0.425289215 0.7178301
## 824  3.250988818 0.9401597
## 825  1.474040521 0.7956646
## 826  1.042008510 0.7615030
## 827  0.479689522 0.7214016
## 828  1.729808504 0.8169777
## 829  1.730276012 0.8170173
## 830  0.539922851 0.7254243
## 831 -0.164068344 0.6833310
## 832  2.488421245 0.8827826
## 833  3.250988818 0.9401597
## 834  2.990409606 0.9234922
## 835  2.383014673 0.8736224
## 836  3.250988818 0.9401597
## 837  2.079493544 0.8470780
## 838  1.821454740 0.8247754
## 839  1.419847034 0.7912441
## 840  0.537985484 0.7252938
## 841  2.582006728 0.8908233
## 842  0.652914823 0.7331576
## 843  1.586088809 0.8049140
## 844  1.854805242 0.8276312
## 845 -0.344251670 0.6745262
## 846  3.004928842 0.9245348
## 847  3.250988818 0.9401597
## 848  0.488669678 0.7219968
## 849  0.642237705 0.7324167
## 850  0.066225366 0.6958380
## 851  1.530203480 0.8002828
## 852  0.309348648 0.7104209
## 853  0.292551514 0.7093710
## 854  1.147559514 0.7696095
## 855  0.711243210 0.7372419
## 856  0.638731015 0.7321738
## 857  0.460713549 0.7201491
## 858 -0.235122542 0.6797512
## 859  1.508547364 0.7984977
## 860 -0.511601532 0.6671911
## 861  1.930459094 0.8341420
## 862  0.735795942 0.7389793
## 863  1.346773205 0.7853413
## 864  1.392530810 0.7890296
## 865  1.878827611 0.8296938
## 866  0.048086700 0.6948049
## 867 -0.064956147 0.6885486
## 868  1.870847867 0.8290082
## 869  3.004928842 0.9245348
## 870 -1.008717575 0.6508049
## 871  1.914931463 0.8328022
## 872  1.544285023 0.8014464
## 873  2.843948887 0.9124165
## 874  1.315952264 0.7828722
## 875  0.563836949 0.7270409
## 876  1.758512986 0.8194118
## 877  2.855236156 0.9133021
## 878  0.411728194 0.7169491
## 879  0.180482731 0.7025243
## 880  1.229581739 0.7760206
## 881  2.070564001 0.8462996
## 882  1.657283721 0.8108635
## 883  1.332499233 0.7841963
## 884  2.663375616 0.8977056
## 885  0.814779660 0.7446400
## 886  1.614811305 0.8073077
## 887  2.286566077 0.8651900
## 888  0.739995292 0.7392776
## 889  1.614811305 0.8073077
## 890  0.517363524 0.7239094
## 891  2.389613871 0.8741980
## 892  0.984985689 0.7571938
## 893  2.265698007 0.8633628
## 894  1.544602455 0.8014726
## 895  0.481968581 0.7215525
## 896  3.250988818 0.9401597
## 897  1.109660069 0.7666797
## 898  1.248766404 0.7775337
## 899  1.580916194 0.8044839
## 900  2.697591743 0.9005602
## 901 -0.325575829 0.6753964
## 902  1.008737290 0.7589826
## 903 -0.100349895 0.6866560
## 904  2.252437921 0.8622016
## 905  2.109610082 0.8497058
## 906 -1.718690626 0.6437481
## 907  1.263470528 0.7786969
## 908  0.753865338 0.7402648
## 909  0.986494847 0.7573072
## 910  1.741203802 0.8179431
## 911  2.568529257 0.8896725
## 912  0.393380057 0.7157631
## 913  2.214982882 0.8589217
## 914  0.466716710 0.7205445
## 915  1.187914970 0.7727519
## 
## 
## $fits
## $fits$original
## 
## Call:
## mirt(data = items, model = model, method = method, verbose = messages, 
##     technical = technical)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 14 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: BFGS 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -10253.71
## Estimated parameters: 48 
## AIC = 20603.41
## BIC = 20834.72; SABIC = 20682.28
## G2 (16777167) = 8490.21, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$noDIF_liberal
## 
## Call:
## mirt(data = items, model = mirt.model(model_noDIF_liberal_Q), 
##     method = method, verbose = messages, technical = technical)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 18 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: BFGS 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -10288.04
## Estimated parameters: 46 
## AIC = 20668.08
## BIC = 20889.75; SABIC = 20743.66
## G2 (16777169) = 8558.87, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$noDIF_conservative
## 
## Call:
## mirt(data = items, model = mirt.model(model_noDIF_conservative_Q), 
##     method = method, verbose = messages, technical = technical)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 14 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: BFGS 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -10253.71
## Estimated parameters: 48 
## AIC = 20603.41
## BIC = 20834.72; SABIC = 20682.28
## G2 (16777167) = 8490.21, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$anchor_liberal
## 
## Call:
## multipleGroup(data = items, model = model, group = group, invariance = c(items_noDIF_liberal %>% 
##     names(), "free_means", "free_var"), method = method, technical = technical, 
##     verbose = messages)
## 
## Full-information item factor analysis with 1 factor(s).
## FAILED TO CONVERGE within 1e-04 tolerance after 500 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: nlminb 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -10238.65
## Estimated parameters: 98 
## AIC = 20585.3
## BIC = 20845.53; SABIC = 20674.03
## G2 (33554376) = 8631.62, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$anchor_conservative
## 
## Call:
## multipleGroup(data = items, model = model, group = group, invariance = c(items_noDIF_conservative %>% 
##     names(), "free_means", "free_var"), method = method, technical = technical, 
##     verbose = messages)
## 
## Full-information item factor analysis with 1 factor(s).
## FAILED TO CONVERGE within 1e-04 tolerance after 500 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: nlminb 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -10248.54
## Estimated parameters: 98 
## AIC = 20597.07
## BIC = 20838.02; SABIC = 20679.22
## G2 (33554380) = 8651.39, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## 
## $DIF_stats
##        item converged    AIC  SABIC     HQ    BIC    X2 df     p number  p_adj
## 1   SynA1_r      TRUE  2.095  5.381  5.774 11.733 1.905  2 0.386      1  9.260
## 2   SynA2_r      TRUE  0.945  4.231  4.623 10.582 3.055  2 0.217      2  5.209
## 3   SynA3_r      TRUE  2.977  6.263  6.656 12.615 1.023  2 0.600      3 14.392
## 4   SynA4_r      TRUE  3.362  6.648  7.041 13.000 0.638  2 0.727      4 17.445
## 5   SynA5_r      TRUE  2.525  5.811  6.204 12.163 1.475  2 0.478      5 11.479
## 6   SynA6_r      TRUE -5.004 -1.718 -1.325  4.634 9.004  2 0.011      6  0.266
## 7   SynA7_r      TRUE  2.409  5.695  6.088 12.047 1.591  2 0.451      7 10.832
## 8   SynA8_r      TRUE -1.008  2.278  2.670  8.629 5.008  2 0.082      8  1.962
## 9   SynA9_r      TRUE  2.398  5.684  6.076 12.035 1.602  2 0.449      9 10.771
## 10 SynA10_r      TRUE  2.595  5.881  6.274 12.233 1.405  2 0.495     10 11.887
## 11 SynA11_r      TRUE  3.745  7.031  7.423 13.382 0.255  2 0.880     11 21.123
## 12 SynA13_r      TRUE -1.204  2.082  2.475  8.434 5.204  2 0.074     12  1.779
## 13 SynA14_r      TRUE  3.425  6.711  7.104 13.063 0.575  2 0.750     13 18.002
## 14 SynA15_r      TRUE  3.275  6.561  6.954 12.913 0.725  2 0.696     14 16.706
## 15 SynA16_r      TRUE -2.123  1.163  1.556  7.515 6.123  2 0.047     15  1.124
## 16 SynA17_r      TRUE  3.853  7.139  7.532 13.491 0.147  2 0.929     16 22.297
## 17 SynA18_r      TRUE  1.644  4.931  5.323 11.282 2.356  2 0.308     17  7.391
## 18 SynA19_r      TRUE  3.389  6.675  7.068 13.027 0.611  2 0.737     18 17.681
## 19 SynA20_r      TRUE  3.821  7.107  7.499 13.458 0.179  2 0.914     19 21.940
## 20 SynA21_r      TRUE  3.661  6.947  7.340 13.299 0.339  2 0.844     20 20.262
## 21 SynA22_r      TRUE  2.469  5.755  6.148 12.107 1.531  2 0.465     21 11.162
## 22 SynA23_r      TRUE  2.789  6.075  6.468 12.427 1.211  2 0.546     22 13.097
## 23 SynA24_r      TRUE  2.276  5.562  5.955 11.914 1.724  2 0.422     23 10.136
## 24 SynA25_r      TRUE  2.343  5.629  6.022 11.981 1.657  2 0.437     24 10.480
## 
## $effect_size_items
## $effect_size_items$liberal
##          SIDS  UIDS   SIDN  UIDN  ESSD theta.of.max.D max.D mean.ES.foc
## item.1  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.915
## item.2  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.888
## item.3  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.863
## item.4  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.944
## item.5  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.834
## item.6  0.548 0.579  0.555 0.583 3.695          2.977 0.867       0.656
## item.7  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.896
## item.8  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.517
## item.9  0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.825
## item.10 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.767
## item.11 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.793
## item.12 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.394
## item.13 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.940
## item.14 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.929
## item.15 0.000 0.093 -0.006 0.087 0.000         -1.014 0.896       0.946
## item.16 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.970
## item.17 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.783
## item.18 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.699
## item.19 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.696
## item.20 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.784
## item.21 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.520
## item.22 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.731
## item.23 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.482
## item.24 0.000 0.000  0.000 0.000 0.000          0.422 0.000       0.497
##         mean.ES.ref
## item.1        0.915
## item.2        0.888
## item.3        0.863
## item.4        0.944
## item.5        0.834
## item.6        0.108
## item.7        0.896
## item.8        0.517
## item.9        0.825
## item.10       0.767
## item.11       0.793
## item.12       0.394
## item.13       0.940
## item.14       0.929
## item.15       0.946
## item.16       0.970
## item.17       0.783
## item.18       0.699
## item.19       0.696
## item.20       0.784
## item.21       0.520
## item.22       0.731
## item.23       0.482
## item.24       0.497
## 
## $effect_size_items$conservative
##         SIDS UIDS SIDN UIDN ESSD theta.of.max.D max.D mean.ES.foc mean.ES.ref
## item.1     0    0    0    0    0          0.634     0       0.916       0.916
## item.2     0    0    0    0    0          0.634     0       0.888       0.888
## item.3     0    0    0    0    0          0.634     0       0.863       0.863
## item.4     0    0    0    0    0          0.634     0       0.944       0.944
## item.5     0    0    0    0    0          0.634     0       0.835       0.835
## item.6     0    0    0    0    0          0.634     0       0.651       0.651
## item.7     0    0    0    0    0          0.634     0       0.897       0.897
## item.8     0    0    0    0    0          0.634     0       0.517       0.517
## item.9     0    0    0    0    0          0.634     0       0.826       0.826
## item.10    0    0    0    0    0          0.634     0       0.768       0.768
## item.11    0    0    0    0    0          0.634     0       0.793       0.793
## item.12    0    0    0    0    0          0.634     0       0.395       0.395
## item.13    0    0    0    0    0          0.634     0       0.940       0.940
## item.14    0    0    0    0    0          0.634     0       0.929       0.929
## item.15    0    0    0    0    0          0.634     0       0.945       0.945
## item.16    0    0    0    0    0          0.634     0       0.970       0.970
## item.17    0    0    0    0    0          0.634     0       0.783       0.783
## item.18    0    0    0    0    0          0.634     0       0.699       0.699
## item.19    0    0    0    0    0          0.634     0       0.696       0.696
## item.20    0    0    0    0    0          0.634     0       0.784       0.784
## item.21    0    0    0    0    0          0.634     0       0.520       0.520
## item.22    0    0    0    0    0          0.634     0       0.732       0.732
## item.23    0    0    0    0    0          0.634     0       0.482       0.482
## item.24    0    0    0    0    0          0.634     0       0.497       0.497
## 
## 
## $effect_size_test
## $effect_size_test$liberal
##           Effect Size     Value
## 1                STDS 0.5484530
## 2                UTDS 0.6713164
## 3              UETSDS 0.5494748
## 4               ETSSD 0.2734043
## 5         Starks.DTFR 0.5489986
## 6               UDTFR 0.6699700
## 7              UETSDN 0.5490045
## 8 theta.of.max.test.D 2.9773741
## 9           Test.Dmax 0.8462547
## 
## $effect_size_test$conservative
##           Effect Size     Value
## 1                STDS 0.0000000
## 2                UTDS 0.0000000
## 3              UETSDS 0.0000000
## 4               ETSSD 0.0000000
## 5         Starks.DTFR 0.0000000
## 6               UDTFR 0.0000000
## 7              UETSDN 0.0000000
## 8 theta.of.max.test.D 0.6342421
## 9           Test.Dmax 0.0000000

Study 1c

s1c_mirt_fit = mirt(
  data = d1c %>% select(PFA1_r:PFA10_r),
  model = 1
)

## 
Iteration: 1, Log-Lik: -5263.765, Max-Change: 0.49473
Iteration: 2, Log-Lik: -5163.070, Max-Change: 0.31897
Iteration: 3, Log-Lik: -5135.390, Max-Change: 0.19696
Iteration: 4, Log-Lik: -5127.324, Max-Change: 0.12312
Iteration: 5, Log-Lik: -5124.734, Max-Change: 0.07460
Iteration: 6, Log-Lik: -5123.869, Max-Change: 0.04649
Iteration: 7, Log-Lik: -5123.474, Max-Change: 0.01870
Iteration: 8, Log-Lik: -5123.425, Max-Change: 0.01149
Iteration: 9, Log-Lik: -5123.407, Max-Change: 0.00649
Iteration: 10, Log-Lik: -5123.399, Max-Change: 0.00334
Iteration: 11, Log-Lik: -5123.397, Max-Change: 0.00233
Iteration: 12, Log-Lik: -5123.397, Max-Change: 0.00124
Iteration: 13, Log-Lik: -5123.396, Max-Change: 0.00041
Iteration: 14, Log-Lik: -5123.396, Max-Change: 0.00035
Iteration: 15, Log-Lik: -5123.396, Max-Change: 0.00029
Iteration: 16, Log-Lik: -5123.396, Max-Change: 0.00018
Iteration: 17, Log-Lik: -5123.396, Max-Change: 0.00015
Iteration: 18, Log-Lik: -5123.396, Max-Change: 0.00012
Iteration: 19, Log-Lik: -5123.396, Max-Change: 0.00008

s1c_mirt_fit %>% summary()

##            F1    h2
## PFA1_r  0.615 0.378
## PFA2_r  0.605 0.366
## PFA3_r  0.433 0.188
## PFA4_r  0.695 0.484
## PFA5_r  0.781 0.610
## PFA6_r  0.737 0.542
## PFA7_r  0.774 0.599
## PFA8_r  0.704 0.495
## PFA9_r  0.382 0.146
## PFA10_r 0.559 0.313
## 
## SS loadings:  4.12 
## Proportion Var:  0.412 
## 
## Factor correlations: 
## 
##    F1
## F1  1

s1c_mirt_fit_scores = fscores(s1c_mirt_fit, full.scores = T, full.scores.SE = T)
d1c$g = s1c_mirt_fit_scores[, 1] %>% standardize(d1c$Race == "White")

#reliability
marginal_rxx(s1c_mirt_fit)

## [1] 0.7497582

empirical_rxx(s1c_mirt_fit_scores)

##        F1 
## 0.7567558

#gaps
GG_group_means(d1c, "g", groupvar = "Race")

mean(d1c$g[d1c$Race=="Black"])

## [1] -0.8456641

#adjust for reliability
mean(d1c$g[d1c$Race=="Black"]) %>% adj_d_reliability(empirical_rxx(s1c_mirt_fit_scores))

##        F1 
## -1.001318

#Jensen method
s1c_items = tibble(
  item = d1c %>% select(PFA1_r:PFA10_r) %>% names(),
  loading = s1c_mirt_fit %>% summary() %>% .$rotF %>% as.vector(),
  black_white_d = map_dbl(d1c %>% select(PFA1_r:PFA10_r), function(x) {
    #pass rates
    pass_black = x[d1c$Race == "Black"] %>% wtd_mean()
    pass_white = x[d1c$Race == "White"] %>% wtd_mean()
    
    #inverse normal d value
    qnorm(pass_white) - qnorm(pass_black)
  })
)

##            F1    h2
## PFA1_r  0.615 0.378
## PFA2_r  0.605 0.366
## PFA3_r  0.433 0.188
## PFA4_r  0.695 0.484
## PFA5_r  0.781 0.610
## PFA6_r  0.737 0.542
## PFA7_r  0.774 0.599
## PFA8_r  0.704 0.495
## PFA9_r  0.382 0.146
## PFA10_r 0.559 0.313
## 
## SS loadings:  4.12 
## Proportion Var:  0.412 
## 
## Factor correlations: 
## 
##    F1
## F1  1

GG_scatter(s1c_items, "loading", "black_white_d", case_names = "item")

## `geom_smooth()` using formula 'y ~ x'

lm(black_white_d ~ loading, data = s1c_items) %>% predict(newdata = data.frame(loading = 1), interval = "confidence")

##         fit       lwr      upr
## 1 0.9820966 0.5900388 1.374155

#test bias DIF
#subset to black-white
d1c_dif = DIF_test(
  items = d1c_bw %>% select(PFA1_r:PFA10_r),
  model = 1,
  group = d1c_bw$Race
)

## There are 8 steps

## Step 1: Initial joint fit

## 
Iteration: 1, Log-Lik: -4044.602, Max-Change: 0.51491
Iteration: 2, Log-Lik: -3954.097, Max-Change: 0.33208
Iteration: 3, Log-Lik: -3930.899, Max-Change: 0.21010
Iteration: 4, Log-Lik: -3924.339, Max-Change: 0.11901
Iteration: 5, Log-Lik: -3922.294, Max-Change: 0.07333
Iteration: 6, Log-Lik: -3921.594, Max-Change: 0.04589
Iteration: 7, Log-Lik: -3921.259, Max-Change: 0.01990
Iteration: 8, Log-Lik: -3921.218, Max-Change: 0.01223
Iteration: 9, Log-Lik: -3921.203, Max-Change: 0.00684
Iteration: 10, Log-Lik: -3921.197, Max-Change: 0.00397
Iteration: 11, Log-Lik: -3921.195, Max-Change: 0.00211
Iteration: 12, Log-Lik: -3921.195, Max-Change: 0.00142
Iteration: 13, Log-Lik: -3921.194, Max-Change: 0.00035
Iteration: 14, Log-Lik: -3921.194, Max-Change: 0.00024
Iteration: 15, Log-Lik: -3921.194, Max-Change: 0.00021
Iteration: 16, Log-Lik: -3921.194, Max-Change: 0.00012
Iteration: 17, Log-Lik: -3921.194, Max-Change: 0.00010
Iteration: 18, Log-Lik: -3921.194, Max-Change: 0.00009

## 
## Step 2: Initial MI fit

## 
Iteration: 1, Log-Lik: -4044.602, Max-Change: 0.51381
Iteration: 2, Log-Lik: -3901.639, Max-Change: 0.29073
Iteration: 3, Log-Lik: -3874.689, Max-Change: 0.15402
Iteration: 4, Log-Lik: -3863.788, Max-Change: 0.10714
Iteration: 5, Log-Lik: -3856.761, Max-Change: 0.09402
Iteration: 6, Log-Lik: -3851.542, Max-Change: 0.08171
Iteration: 7, Log-Lik: -3847.477, Max-Change: 0.07088
Iteration: 8, Log-Lik: -3844.237, Max-Change: 0.06154
Iteration: 9, Log-Lik: -3841.616, Max-Change: 0.05352
Iteration: 10, Log-Lik: -3836.903, Max-Change: 0.16050
Iteration: 11, Log-Lik: -3832.336, Max-Change: 0.03079
Iteration: 12, Log-Lik: -3831.673, Max-Change: 0.02895
Iteration: 13, Log-Lik: -3830.543, Max-Change: 0.06625
Iteration: 14, Log-Lik: -3829.480, Max-Change: 0.03959
Iteration: 15, Log-Lik: -3829.130, Max-Change: 0.03219
Iteration: 16, Log-Lik: -3828.590, Max-Change: 0.04822
Iteration: 17, Log-Lik: -3828.231, Max-Change: 0.03190
Iteration: 18, Log-Lik: -3828.019, Max-Change: 0.02698
Iteration: 19, Log-Lik: -3827.733, Max-Change: 0.05956
Iteration: 20, Log-Lik: -3827.289, Max-Change: 0.03131
Iteration: 21, Log-Lik: -3827.168, Max-Change: 0.02340
Iteration: 22, Log-Lik: -3827.021, Max-Change: 0.02807
Iteration: 23, Log-Lik: -3826.922, Max-Change: 0.01973
Iteration: 24, Log-Lik: -3826.850, Max-Change: 0.01687
Iteration: 25, Log-Lik: -3826.775, Max-Change: 0.04095
Iteration: 26, Log-Lik: -3826.594, Max-Change: 0.01951
Iteration: 27, Log-Lik: -3826.551, Max-Change: 0.01365
Iteration: 28, Log-Lik: -3826.509, Max-Change: 0.01411
Iteration: 29, Log-Lik: -3826.478, Max-Change: 0.01049
Iteration: 30, Log-Lik: -3826.453, Max-Change: 0.00908
Iteration: 31, Log-Lik: -3826.429, Max-Change: 0.02242
Iteration: 32, Log-Lik: -3826.368, Max-Change: 0.01032
Iteration: 33, Log-Lik: -3826.352, Max-Change: 0.00709
Iteration: 34, Log-Lik: -3826.338, Max-Change: 0.00714
Iteration: 35, Log-Lik: -3826.326, Max-Change: 0.00532
Iteration: 36, Log-Lik: -3826.318, Max-Change: 0.00459
Iteration: 37, Log-Lik: -3826.309, Max-Change: 0.01132
Iteration: 38, Log-Lik: -3826.287, Max-Change: 0.00517
Iteration: 39, Log-Lik: -3826.281, Max-Change: 0.00351
Iteration: 40, Log-Lik: -3826.276, Max-Change: 0.00352
Iteration: 41, Log-Lik: -3826.271, Max-Change: 0.00261
Iteration: 42, Log-Lik: -3826.268, Max-Change: 0.00225
Iteration: 43, Log-Lik: -3826.264, Max-Change: 0.00556
Iteration: 44, Log-Lik: -3826.256, Max-Change: 0.00251
Iteration: 45, Log-Lik: -3826.253, Max-Change: 0.00171
Iteration: 46, Log-Lik: -3826.251, Max-Change: 0.00172
Iteration: 47, Log-Lik: -3826.249, Max-Change: 0.00126
Iteration: 48, Log-Lik: -3826.247, Max-Change: 0.00108
Iteration: 49, Log-Lik: -3826.246, Max-Change: 0.00267
Iteration: 50, Log-Lik: -3826.242, Max-Change: 0.00121
Iteration: 51, Log-Lik: -3826.241, Max-Change: 0.00081
Iteration: 52, Log-Lik: -3826.240, Max-Change: 0.00081
Iteration: 53, Log-Lik: -3826.239, Max-Change: 0.00060
Iteration: 54, Log-Lik: -3826.239, Max-Change: 0.00052
Iteration: 55, Log-Lik: -3826.238, Max-Change: 0.00126
Iteration: 56, Log-Lik: -3826.236, Max-Change: 0.00059
Iteration: 57, Log-Lik: -3826.236, Max-Change: 0.00040
Iteration: 58, Log-Lik: -3826.235, Max-Change: 0.00039
Iteration: 59, Log-Lik: -3826.235, Max-Change: 0.00029
Iteration: 60, Log-Lik: -3826.235, Max-Change: 0.00025
Iteration: 61, Log-Lik: -3826.234, Max-Change: 0.00061
Iteration: 62, Log-Lik: -3826.234, Max-Change: 0.00027
Iteration: 63, Log-Lik: -3826.233, Max-Change: 0.00019
Iteration: 64, Log-Lik: -3826.233, Max-Change: 0.00020
Iteration: 65, Log-Lik: -3826.233, Max-Change: 0.00014
Iteration: 66, Log-Lik: -3826.233, Max-Change: 0.00012
Iteration: 67, Log-Lik: -3826.233, Max-Change: 0.00027
Iteration: 68, Log-Lik: -3826.232, Max-Change: 0.00013
Iteration: 69, Log-Lik: -3826.232, Max-Change: 0.00008

## 
## Step 3: Leave one out MI testing

## 
## Step 4: Fit without DIF items, liberal threshold

## 
Iteration: 1, Log-Lik: -4142.432, Max-Change: 0.57444
Iteration: 2, Log-Lik: -4055.256, Max-Change: 0.39541
Iteration: 3, Log-Lik: -4031.736, Max-Change: 0.25326
Iteration: 4, Log-Lik: -4024.673, Max-Change: 0.16255
Iteration: 5, Log-Lik: -4022.421, Max-Change: 0.09629
Iteration: 6, Log-Lik: -4021.672, Max-Change: 0.06404
Iteration: 7, Log-Lik: -4021.318, Max-Change: 0.02814
Iteration: 8, Log-Lik: -4021.277, Max-Change: 0.01754
Iteration: 9, Log-Lik: -4021.262, Max-Change: 0.00940
Iteration: 10, Log-Lik: -4021.256, Max-Change: 0.00627
Iteration: 11, Log-Lik: -4021.254, Max-Change: 0.00349
Iteration: 12, Log-Lik: -4021.254, Max-Change: 0.00265
Iteration: 13, Log-Lik: -4021.253, Max-Change: 0.00111
Iteration: 14, Log-Lik: -4021.253, Max-Change: 0.00050
Iteration: 15, Log-Lik: -4021.253, Max-Change: 0.00030
Iteration: 16, Log-Lik: -4021.253, Max-Change: 0.00028
Iteration: 17, Log-Lik: -4021.253, Max-Change: 0.00025
Iteration: 18, Log-Lik: -4021.253, Max-Change: 0.00023
Iteration: 19, Log-Lik: -4021.253, Max-Change: 0.00055
Iteration: 20, Log-Lik: -4021.253, Max-Change: 0.00006

## 
## Step 5: Fit without DIF items, conservative threshold

## 
Iteration: 1, Log-Lik: -4138.619, Max-Change: 0.53983
Iteration: 2, Log-Lik: -4049.268, Max-Change: 0.38294
Iteration: 3, Log-Lik: -4025.295, Max-Change: 0.24741
Iteration: 4, Log-Lik: -4018.407, Max-Change: 0.16632
Iteration: 5, Log-Lik: -4016.142, Max-Change: 0.09168
Iteration: 6, Log-Lik: -4015.453, Max-Change: 0.06105
Iteration: 7, Log-Lik: -4015.125, Max-Change: 0.02724
Iteration: 8, Log-Lik: -4015.085, Max-Change: 0.01727
Iteration: 9, Log-Lik: -4015.070, Max-Change: 0.01030
Iteration: 10, Log-Lik: -4015.063, Max-Change: 0.00441
Iteration: 11, Log-Lik: -4015.062, Max-Change: 0.00356
Iteration: 12, Log-Lik: -4015.062, Max-Change: 0.00248
Iteration: 13, Log-Lik: -4015.061, Max-Change: 0.00126
Iteration: 14, Log-Lik: -4015.061, Max-Change: 0.00044
Iteration: 15, Log-Lik: -4015.061, Max-Change: 0.00032
Iteration: 16, Log-Lik: -4015.061, Max-Change: 0.00152
Iteration: 17, Log-Lik: -4015.061, Max-Change: 0.00077
Iteration: 18, Log-Lik: -4015.061, Max-Change: 0.00009

## 
## Step 6: Fit with anchor items, liberal threshold

## 
Iteration: 1, Log-Lik: -4044.602, Max-Change: 0.53337
Iteration: 2, Log-Lik: -3879.135, Max-Change: 0.29255
Iteration: 3, Log-Lik: -3850.145, Max-Change: 0.15687
Iteration: 4, Log-Lik: -3839.285, Max-Change: 0.10647
Iteration: 5, Log-Lik: -3832.529, Max-Change: 0.09353
Iteration: 6, Log-Lik: -3827.587, Max-Change: 0.08141
Iteration: 7, Log-Lik: -3823.783, Max-Change: 0.07073
Iteration: 8, Log-Lik: -3820.787, Max-Change: 0.06155
Iteration: 9, Log-Lik: -3818.393, Max-Change: 0.05365
Iteration: 10, Log-Lik: -3813.997, Max-Change: 0.14443
Iteration: 11, Log-Lik: -3810.077, Max-Change: 0.02609
Iteration: 12, Log-Lik: -3809.527, Max-Change: 0.01780
Iteration: 13, Log-Lik: -3808.622, Max-Change: 0.03743
Iteration: 14, Log-Lik: -3808.141, Max-Change: 0.02089
Iteration: 15, Log-Lik: -3807.834, Max-Change: 0.01916
Iteration: 16, Log-Lik: -3807.339, Max-Change: 0.05359
Iteration: 17, Log-Lik: -3806.607, Max-Change: 0.02559
Iteration: 18, Log-Lik: -3806.443, Max-Change: 0.02051
Iteration: 19, Log-Lik: -3806.225, Max-Change: 0.02609
Iteration: 20, Log-Lik: -3806.088, Max-Change: 0.01882
Iteration: 21, Log-Lik: -3805.978, Max-Change: 0.01692
Iteration: 22, Log-Lik: -3805.844, Max-Change: 0.04578
Iteration: 23, Log-Lik: -3805.549, Max-Change: 0.02069
Iteration: 24, Log-Lik: -3805.484, Max-Change: 0.01541
Iteration: 25, Log-Lik: -3805.410, Max-Change: 0.01712
Iteration: 26, Log-Lik: -3805.360, Max-Change: 0.01293
Iteration: 27, Log-Lik: -3805.318, Max-Change: 0.01161
Iteration: 28, Log-Lik: -3805.270, Max-Change: 0.03143
Iteration: 29, Log-Lik: -3805.156, Max-Change: 0.01370
Iteration: 30, Log-Lik: -3805.130, Max-Change: 0.00996
Iteration: 31, Log-Lik: -3805.103, Max-Change: 0.01076
Iteration: 32, Log-Lik: -3805.083, Max-Change: 0.00813
Iteration: 33, Log-Lik: -3805.067, Max-Change: 0.00727
Iteration: 34, Log-Lik: -3805.049, Max-Change: 0.01961
Iteration: 35, Log-Lik: -3805.005, Max-Change: 0.00841
Iteration: 36, Log-Lik: -3804.994, Max-Change: 0.00605
Iteration: 37, Log-Lik: -3804.984, Max-Change: 0.00655
Iteration: 38, Log-Lik: -3804.975, Max-Change: 0.00488
Iteration: 39, Log-Lik: -3804.969, Max-Change: 0.00435
Iteration: 40, Log-Lik: -3804.962, Max-Change: 0.01170
Iteration: 41, Log-Lik: -3804.944, Max-Change: 0.00496
Iteration: 42, Log-Lik: -3804.940, Max-Change: 0.00356
Iteration: 43, Log-Lik: -3804.936, Max-Change: 0.00385
Iteration: 44, Log-Lik: -3804.932, Max-Change: 0.00285
Iteration: 45, Log-Lik: -3804.929, Max-Change: 0.00253
Iteration: 46, Log-Lik: -3804.927, Max-Change: 0.00679
Iteration: 47, Log-Lik: -3804.919, Max-Change: 0.00286
Iteration: 48, Log-Lik: -3804.917, Max-Change: 0.00205
Iteration: 49, Log-Lik: -3804.915, Max-Change: 0.00226
Iteration: 50, Log-Lik: -3804.914, Max-Change: 0.00164
Iteration: 51, Log-Lik: -3804.912, Max-Change: 0.00144
Iteration: 52, Log-Lik: -3804.911, Max-Change: 0.00388
Iteration: 53, Log-Lik: -3804.908, Max-Change: 0.00163
Iteration: 54, Log-Lik: -3804.907, Max-Change: 0.00117
Iteration: 55, Log-Lik: -3804.906, Max-Change: 0.00130
Iteration: 56, Log-Lik: -3804.905, Max-Change: 0.00093
Iteration: 57, Log-Lik: -3804.905, Max-Change: 0.00082
Iteration: 58, Log-Lik: -3804.904, Max-Change: 0.00218
Iteration: 59, Log-Lik: -3804.902, Max-Change: 0.00092
Iteration: 60, Log-Lik: -3804.902, Max-Change: 0.00066
Iteration: 61, Log-Lik: -3804.902, Max-Change: 0.00075
Iteration: 62, Log-Lik: -3804.901, Max-Change: 0.00052
Iteration: 63, Log-Lik: -3804.901, Max-Change: 0.00046
Iteration: 64, Log-Lik: -3804.900, Max-Change: 0.00121
Iteration: 65, Log-Lik: -3804.900, Max-Change: 0.00052
Iteration: 66, Log-Lik: -3804.899, Max-Change: 0.00037
Iteration: 67, Log-Lik: -3804.899, Max-Change: 0.00044
Iteration: 68, Log-Lik: -3804.899, Max-Change: 0.00029
Iteration: 69, Log-Lik: -3804.899, Max-Change: 0.00026
Iteration: 70, Log-Lik: -3804.899, Max-Change: 0.00067
Iteration: 71, Log-Lik: -3804.898, Max-Change: 0.00029
Iteration: 72, Log-Lik: -3804.898, Max-Change: 0.00021
Iteration: 73, Log-Lik: -3804.898, Max-Change: 0.00026
Iteration: 74, Log-Lik: -3804.898, Max-Change: 0.00016
Iteration: 75, Log-Lik: -3804.898, Max-Change: 0.00014
Iteration: 76, Log-Lik: -3804.898, Max-Change: 0.00037
Iteration: 77, Log-Lik: -3804.897, Max-Change: 0.00016
Iteration: 78, Log-Lik: -3804.897, Max-Change: 0.00012
Iteration: 79, Log-Lik: -3804.897, Max-Change: 0.00015
Iteration: 80, Log-Lik: -3804.897, Max-Change: 0.00010

## 
## Step 7: Fit with anchor items, conservative threshold

## 
Iteration: 1, Log-Lik: -4044.602, Max-Change: 0.53337
Iteration: 2, Log-Lik: -3881.862, Max-Change: 0.29770
Iteration: 3, Log-Lik: -3853.255, Max-Change: 0.16116
Iteration: 4, Log-Lik: -3842.534, Max-Change: 0.10871
Iteration: 5, Log-Lik: -3835.832, Max-Change: 0.09207
Iteration: 6, Log-Lik: -3830.901, Max-Change: 0.08002
Iteration: 7, Log-Lik: -3827.086, Max-Change: 0.06951
Iteration: 8, Log-Lik: -3824.068, Max-Change: 0.06047
Iteration: 9, Log-Lik: -3821.647, Max-Change: 0.05273
Iteration: 10, Log-Lik: -3817.213, Max-Change: 0.14880
Iteration: 11, Log-Lik: -3813.190, Max-Change: 0.02718
Iteration: 12, Log-Lik: -3812.620, Max-Change: 0.01863
Iteration: 13, Log-Lik: -3811.683, Max-Change: 0.03938
Iteration: 14, Log-Lik: -3811.170, Max-Change: 0.02460
Iteration: 15, Log-Lik: -3810.850, Max-Change: 0.02211
Iteration: 16, Log-Lik: -3810.350, Max-Change: 0.05588
Iteration: 17, Log-Lik: -3809.612, Max-Change: 0.02901
Iteration: 18, Log-Lik: -3809.440, Max-Change: 0.02287
Iteration: 19, Log-Lik: -3809.211, Max-Change: 0.02917
Iteration: 20, Log-Lik: -3809.066, Max-Change: 0.02082
Iteration: 21, Log-Lik: -3808.955, Max-Change: 0.01841
Iteration: 22, Log-Lik: -3808.824, Max-Change: 0.04772
Iteration: 23, Log-Lik: -3808.531, Max-Change: 0.02235
Iteration: 24, Log-Lik: -3808.465, Max-Change: 0.01639
Iteration: 25, Log-Lik: -3808.392, Max-Change: 0.01810
Iteration: 26, Log-Lik: -3808.342, Max-Change: 0.01354
Iteration: 27, Log-Lik: -3808.301, Max-Change: 0.01202
Iteration: 28, Log-Lik: -3808.257, Max-Change: 0.03129
Iteration: 29, Log-Lik: -3808.149, Max-Change: 0.01409
Iteration: 30, Log-Lik: -3808.123, Max-Change: 0.01009
Iteration: 31, Log-Lik: -3808.098, Max-Change: 0.01082
Iteration: 32, Log-Lik: -3808.079, Max-Change: 0.00810
Iteration: 33, Log-Lik: -3808.063, Max-Change: 0.00716
Iteration: 34, Log-Lik: -3808.047, Max-Change: 0.01863
Iteration: 35, Log-Lik: -3808.007, Max-Change: 0.00822
Iteration: 36, Log-Lik: -3807.997, Max-Change: 0.00583
Iteration: 37, Log-Lik: -3807.987, Max-Change: 0.00619
Iteration: 38, Log-Lik: -3807.980, Max-Change: 0.00461
Iteration: 39, Log-Lik: -3807.974, Max-Change: 0.00406
Iteration: 40, Log-Lik: -3807.968, Max-Change: 0.01059
Iteration: 41, Log-Lik: -3807.952, Max-Change: 0.00461
Iteration: 42, Log-Lik: -3807.947, Max-Change: 0.00326
Iteration: 43, Log-Lik: -3807.944, Max-Change: 0.00347
Iteration: 44, Log-Lik: -3807.940, Max-Change: 0.00256
Iteration: 45, Log-Lik: -3807.938, Max-Change: 0.00225
Iteration: 46, Log-Lik: -3807.935, Max-Change: 0.00584
Iteration: 47, Log-Lik: -3807.929, Max-Change: 0.00254
Iteration: 48, Log-Lik: -3807.927, Max-Change: 0.00179
Iteration: 49, Log-Lik: -3807.925, Max-Change: 0.00190
Iteration: 50, Log-Lik: -3807.924, Max-Change: 0.00140
Iteration: 51, Log-Lik: -3807.922, Max-Change: 0.00122
Iteration: 52, Log-Lik: -3807.921, Max-Change: 0.00316
Iteration: 53, Log-Lik: -3807.918, Max-Change: 0.00138
Iteration: 54, Log-Lik: -3807.917, Max-Change: 0.00097
Iteration: 55, Log-Lik: -3807.917, Max-Change: 0.00104
Iteration: 56, Log-Lik: -3807.916, Max-Change: 0.00076
Iteration: 57, Log-Lik: -3807.915, Max-Change: 0.00066
Iteration: 58, Log-Lik: -3807.915, Max-Change: 0.00172
Iteration: 59, Log-Lik: -3807.913, Max-Change: 0.00075
Iteration: 60, Log-Lik: -3807.913, Max-Change: 0.00053
Iteration: 61, Log-Lik: -3807.913, Max-Change: 0.00057
Iteration: 62, Log-Lik: -3807.912, Max-Change: 0.00041
Iteration: 63, Log-Lik: -3807.912, Max-Change: 0.00036
Iteration: 64, Log-Lik: -3807.912, Max-Change: 0.00093
Iteration: 65, Log-Lik: -3807.911, Max-Change: 0.00041
Iteration: 66, Log-Lik: -3807.911, Max-Change: 0.00028
Iteration: 67, Log-Lik: -3807.910, Max-Change: 0.00031
Iteration: 68, Log-Lik: -3807.910, Max-Change: 0.00022
Iteration: 69, Log-Lik: -3807.910, Max-Change: 0.00019
Iteration: 70, Log-Lik: -3807.910, Max-Change: 0.00048
Iteration: 71, Log-Lik: -3807.910, Max-Change: 0.00021
Iteration: 72, Log-Lik: -3807.909, Max-Change: 0.00016
Iteration: 73, Log-Lik: -3807.909, Max-Change: 0.00018
Iteration: 74, Log-Lik: -3807.909, Max-Change: 0.00012
Iteration: 75, Log-Lik: -3807.909, Max-Change: 0.00011
Iteration: 76, Log-Lik: -3807.909, Max-Change: 0.00025
Iteration: 77, Log-Lik: -3807.909, Max-Change: 0.00011
Iteration: 78, Log-Lik: -3807.909, Max-Change: 0.00009

## 
## Step 8: Get scores

d1c_dif$effect_size_items

## $liberal
##           SIDS  UIDS   SIDN  UIDN   ESSD theta.of.max.D  max.D mean.ES.foc
## item.1   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.923
## item.2   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.636
## item.3   0.274 0.279  0.285 0.288  2.011          3.817  0.453       0.685
## item.4   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.664
## item.5   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.628
## item.6   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.733
## item.7   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.290
## item.8   0.000 0.000  0.000 0.000  0.000          1.318  0.000       0.491
## item.9   0.044 0.061  0.037 0.049  0.844          3.817  0.270       0.094
## item.10 -0.154 0.154 -0.159 0.159 -0.753          2.809 -0.257       0.212
##         mean.ES.ref
## item.1        0.923
## item.2        0.636
## item.3        0.411
## item.4        0.664
## item.5        0.628
## item.6        0.733
## item.7        0.290
## item.8        0.491
## item.9        0.050
## item.10       0.366
## 
## $conservative
##           SIDS  UIDS   SIDN  UIDN   ESSD theta.of.max.D  max.D mean.ES.foc
## item.1   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.921
## item.2   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.636
## item.3   0.277 0.282  0.289 0.291  2.029          3.793  0.459       0.686
## item.4   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.663
## item.5   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.628
## item.6   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.733
## item.7   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.292
## item.8   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.492
## item.9   0.000 0.000  0.000 0.000  0.000          1.340  0.000       0.101
## item.10 -0.170 0.170 -0.174 0.174 -0.797          2.883 -0.300       0.212
##         mean.ES.ref
## item.1        0.921
## item.2        0.636
## item.3        0.409
## item.4        0.663
## item.5        0.628
## item.6        0.733
## item.7        0.292
## item.8        0.492
## item.9        0.101
## item.10       0.382

d1c_dif$effect_size_test

## $liberal
##           Effect Size      Value
## 1                STDS 0.16375673
## 2                UTDS 0.49385155
## 3              UETSDS 0.17983242
## 4               ETSSD 0.08408709
## 5         Starks.DTFR 0.16313071
## 6               UDTFR 0.49629776
## 7              UETSDN 0.17335020
## 8 theta.of.max.test.D 3.81729698
## 9           Test.Dmax 0.51590773
## 
## $conservative
##           Effect Size      Value
## 1                STDS 0.10697580
## 2                UTDS 0.45125453
## 3              UETSDS 0.11409282
## 4               ETSSD 0.05388974
## 5         Starks.DTFR 0.11432673
## 6               UDTFR 0.46573516
## 7              UETSDN 0.11836668
## 8 theta.of.max.test.D 3.79343001
## 9           Test.Dmax 0.20424877

d1c_dif$fits$anchor_conservative %>% empirical_ES(plot = T)

d1c_dif$fits$anchor_conservative %>% empirical_ES(plot = T, DIF = F)

Study 2-4

#cog data
d234_cog = d234 %>% select(PFA1_r:PFB10_r)

s234_mirt_fit = mirt(
  data = d234_cog,
  model = 1
)

## 
Iteration: 1, Log-Lik: -12803.104, Max-Change: 0.76178
Iteration: 2, Log-Lik: -12549.963, Max-Change: 0.29308
Iteration: 3, Log-Lik: -12513.591, Max-Change: 0.18019
Iteration: 4, Log-Lik: -12504.597, Max-Change: 0.12259
Iteration: 5, Log-Lik: -12499.949, Max-Change: 0.06363
Iteration: 6, Log-Lik: -12498.493, Max-Change: 0.05329
Iteration: 7, Log-Lik: -12497.587, Max-Change: 0.02630
Iteration: 8, Log-Lik: -12497.265, Max-Change: 0.01591
Iteration: 9, Log-Lik: -12497.138, Max-Change: 0.01091
Iteration: 10, Log-Lik: -12497.031, Max-Change: 0.00526
Iteration: 11, Log-Lik: -12497.006, Max-Change: 0.00353
Iteration: 12, Log-Lik: -12496.992, Max-Change: 0.00377
Iteration: 13, Log-Lik: -12496.969, Max-Change: 0.00338
Iteration: 14, Log-Lik: -12496.965, Max-Change: 0.00155
Iteration: 15, Log-Lik: -12496.963, Max-Change: 0.00112
Iteration: 16, Log-Lik: -12496.962, Max-Change: 0.00095
Iteration: 17, Log-Lik: -12496.961, Max-Change: 0.00022
Iteration: 18, Log-Lik: -12496.961, Max-Change: 0.00069
Iteration: 19, Log-Lik: -12496.961, Max-Change: 0.00029
Iteration: 20, Log-Lik: -12496.961, Max-Change: 0.00076
Iteration: 21, Log-Lik: -12496.961, Max-Change: 0.00019
Iteration: 22, Log-Lik: -12496.961, Max-Change: 0.00018
Iteration: 23, Log-Lik: -12496.961, Max-Change: 0.00043
Iteration: 24, Log-Lik: -12496.961, Max-Change: 0.00071
Iteration: 25, Log-Lik: -12496.961, Max-Change: 0.00048
Iteration: 26, Log-Lik: -12496.961, Max-Change: 0.00015
Iteration: 27, Log-Lik: -12496.961, Max-Change: 0.00040
Iteration: 28, Log-Lik: -12496.961, Max-Change: 0.00018
Iteration: 29, Log-Lik: -12496.961, Max-Change: 0.00045
Iteration: 30, Log-Lik: -12496.960, Max-Change: 0.00013
Iteration: 31, Log-Lik: -12496.960, Max-Change: 0.00012
Iteration: 32, Log-Lik: -12496.960, Max-Change: 0.00031
Iteration: 33, Log-Lik: -12496.960, Max-Change: 0.00008

s234_mirt_fit %>% summary()

##            F1     h2
## PFA1_r  0.657 0.4315
## PFA2_r  0.678 0.4603
## PFA3_r  0.531 0.2820
## PFA4_r  0.605 0.3661
## PFA5_r  0.745 0.5549
## PFA6_r  0.698 0.4869
## PFA7_r  0.627 0.3929
## PFA8_r  0.572 0.3268
## PFA9_r  0.560 0.3140
## PFA10_r 0.428 0.1833
## PFB1_r  0.559 0.3125
## PFB2_r  0.807 0.6509
## PFB3_r  0.789 0.6221
## PFB4_r  0.736 0.5415
## PFB5_r  0.242 0.0586
## PFB6_r  0.782 0.6117
## PFB7_r  0.667 0.4449
## PFB8_r  0.439 0.1924
## PFB9_r  0.543 0.2952
## PFB10_r 0.544 0.2962
## 
## SS loadings:  7.825 
## Proportion Var:  0.391 
## 
## Factor correlations: 
## 
##    F1
## F1  1

s234_mirt_fit_scores = fscores(s234_mirt_fit, full.scores = T, full.scores.SE = T)
d234$g = s234_mirt_fit_scores[, 1] %>% standardize(d234$Race == "White")

#reliability
marginal_rxx(s234_mirt_fit)

## [1] 0.8261637

empirical_rxx(s234_mirt_fit_scores)

##        F1 
## 0.8314929

#gaps
GG_group_means(d234, "g", groupvar = "Race")

describeBy(d234$g, d234$Race, mat = T)

mean(d234$g[d234$Race=="Black"])

## [1] -0.786393

#adjust for reliability
mean(d234$g[d234$Race=="Black"]) %>% adj_d_reliability(empirical_rxx(s234_mirt_fit_scores))

##         F1 
## -0.8762393

#Jensen method
s234_items = tibble(
  item = d234 %>% select(PFA1_r:PFB10_r) %>% names(),
  loading = s234_mirt_fit %>% summary() %>% .$rotF %>% as.vector(),
  black_white_d = map_dbl(d234 %>% select(PFA1_r:PFB10_r), function(x) {
    #pass rates
    pass_black = x[d234$Race == "Black"] %>% wtd_mean()
    pass_white = x[d234$Race == "White"] %>% wtd_mean()
    
    #inverse normal d value
    qnorm(pass_white) - qnorm(pass_black)
  })
)

##            F1     h2
## PFA1_r  0.657 0.4315
## PFA2_r  0.678 0.4603
## PFA3_r  0.531 0.2820
## PFA4_r  0.605 0.3661
## PFA5_r  0.745 0.5549
## PFA6_r  0.698 0.4869
## PFA7_r  0.627 0.3929
## PFA8_r  0.572 0.3268
## PFA9_r  0.560 0.3140
## PFA10_r 0.428 0.1833
## PFB1_r  0.559 0.3125
## PFB2_r  0.807 0.6509
## PFB3_r  0.789 0.6221
## PFB4_r  0.736 0.5415
## PFB5_r  0.242 0.0586
## PFB6_r  0.782 0.6117
## PFB7_r  0.667 0.4449
## PFB8_r  0.439 0.1924
## PFB9_r  0.543 0.2952
## PFB10_r 0.544 0.2962
## 
## SS loadings:  7.825 
## Proportion Var:  0.391 
## 
## Factor correlations: 
## 
##    F1
## F1  1

GG_scatter(s234_items %>% filter(is.finite(black_white_d)), "loading", "black_white_d", case_names = "item")

## `geom_smooth()` using formula 'y ~ x'

lm(black_white_d ~ loading, data = s234_items %>% filter(is.finite(black_white_d))) %>% predict(newdata = data.frame(loading = 1), interval = "confidence")

##         fit       lwr      upr
## 1 0.7268147 0.4355339 1.018096

#test bias DIF
#subset to black-white
DIF_test(
  items = d234_bw %>% select(PFA1_r:PFB10_r),
  model = 1,
  group = d234_bw$Race
)

## There are 8 steps

## Step 1: Initial joint fit

## 
Iteration: 1, Log-Lik: -11709.945, Max-Change: 0.64135
Iteration: 2, Log-Lik: -11493.746, Max-Change: 0.29276
Iteration: 3, Log-Lik: -11458.503, Max-Change: 0.24005
Iteration: 4, Log-Lik: -11444.588, Max-Change: 0.11297
Iteration: 5, Log-Lik: -11440.296, Max-Change: 0.07114
Iteration: 6, Log-Lik: -11438.606, Max-Change: 0.05519
Iteration: 7, Log-Lik: -11437.501, Max-Change: 0.02367
Iteration: 8, Log-Lik: -11437.281, Max-Change: 0.01407
Iteration: 9, Log-Lik: -11437.192, Max-Change: 0.00843
Iteration: 10, Log-Lik: -11437.133, Max-Change: 0.00472
Iteration: 11, Log-Lik: -11437.115, Max-Change: 0.00276
Iteration: 12, Log-Lik: -11437.107, Max-Change: 0.00167
Iteration: 13, Log-Lik: -11437.100, Max-Change: 0.00107
Iteration: 14, Log-Lik: -11437.097, Max-Change: 0.00083
Iteration: 15, Log-Lik: -11437.095, Max-Change: 0.00075
Iteration: 16, Log-Lik: -11437.087, Max-Change: 0.00069
Iteration: 17, Log-Lik: -11437.087, Max-Change: 0.00048
Iteration: 18, Log-Lik: -11437.087, Max-Change: 0.00036
Iteration: 19, Log-Lik: -11437.087, Max-Change: 0.00043
Iteration: 20, Log-Lik: -11437.086, Max-Change: 0.00045
Iteration: 21, Log-Lik: -11437.086, Max-Change: 0.00061
Iteration: 22, Log-Lik: -11437.086, Max-Change: 0.00022
Iteration: 23, Log-Lik: -11437.086, Max-Change: 0.00031
Iteration: 24, Log-Lik: -11437.086, Max-Change: 0.00034
Iteration: 25, Log-Lik: -11437.086, Max-Change: 0.00021
Iteration: 26, Log-Lik: -11437.086, Max-Change: 0.00022
Iteration: 27, Log-Lik: -11437.086, Max-Change: 0.00029
Iteration: 28, Log-Lik: -11437.086, Max-Change: 0.00013
Iteration: 29, Log-Lik: -11437.086, Max-Change: 0.00017
Iteration: 30, Log-Lik: -11437.086, Max-Change: 0.00019
Iteration: 31, Log-Lik: -11437.086, Max-Change: 0.00010
Iteration: 32, Log-Lik: -11437.086, Max-Change: 0.00012
Iteration: 33, Log-Lik: -11437.086, Max-Change: 0.00015
Iteration: 34, Log-Lik: -11437.086, Max-Change: 0.00007

## 
## Step 2: Initial MI fit

## 
Iteration: 1, Log-Lik: -11709.945, Max-Change: 0.53950
Iteration: 2, Log-Lik: -11462.959, Max-Change: 0.23412
Iteration: 3, Log-Lik: -11441.830, Max-Change: 0.10408
Iteration: 4, Log-Lik: -11439.093, Max-Change: 0.04927
Iteration: 5, Log-Lik: -11438.528, Max-Change: 0.02438
Iteration: 6, Log-Lik: -11438.331, Max-Change: 0.01260
Iteration: 7, Log-Lik: -11438.201, Max-Change: 0.00668
Iteration: 8, Log-Lik: -11438.094, Max-Change: 0.00604
Iteration: 9, Log-Lik: -11437.992, Max-Change: 0.00640
Iteration: 10, Log-Lik: -11437.630, Max-Change: 0.02013
Iteration: 11, Log-Lik: -11437.382, Max-Change: 0.00766
Iteration: 12, Log-Lik: -11437.289, Max-Change: 0.00729
Iteration: 13, Log-Lik: -11436.957, Max-Change: 0.01915
Iteration: 14, Log-Lik: -11436.731, Max-Change: 0.00636
Iteration: 15, Log-Lik: -11436.646, Max-Change: 0.00657
Iteration: 16, Log-Lik: -11436.341, Max-Change: 0.01829
Iteration: 17, Log-Lik: -11436.134, Max-Change: 0.00661
Iteration: 18, Log-Lik: -11436.056, Max-Change: 0.00657
Iteration: 19, Log-Lik: -11435.777, Max-Change: 0.01745
Iteration: 20, Log-Lik: -11435.587, Max-Change: 0.00617
Iteration: 21, Log-Lik: -11435.516, Max-Change: 0.00627
Iteration: 22, Log-Lik: -11435.259, Max-Change: 0.01671
Iteration: 23, Log-Lik: -11435.084, Max-Change: 0.00606
Iteration: 24, Log-Lik: -11435.018, Max-Change: 0.00610
Iteration: 25, Log-Lik: -11434.782, Max-Change: 0.01602
Iteration: 26, Log-Lik: -11434.621, Max-Change: 0.00582
Iteration: 27, Log-Lik: -11434.561, Max-Change: 0.00589
Iteration: 28, Log-Lik: -11434.342, Max-Change: 0.01536
Iteration: 29, Log-Lik: -11434.194, Max-Change: 0.00565
Iteration: 30, Log-Lik: -11434.138, Max-Change: 0.00571
Iteration: 31, Log-Lik: -11433.937, Max-Change: 0.01474
Iteration: 32, Log-Lik: -11433.800, Max-Change: 0.00545
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Iteration: 481, Log-Lik: -11427.482, Max-Change: 0.00042
Iteration: 482, Log-Lik: -11427.482, Max-Change: 0.00012
Iteration: 483, Log-Lik: -11427.482, Max-Change: 0.00010

## 
## Step 3: Leave one out MI testing

## 
## Step 4: Fit without DIF items, liberal threshold

## 
Iteration: 1, Log-Lik: -11709.945, Max-Change: 0.64135
Iteration: 2, Log-Lik: -11493.746, Max-Change: 0.29276
Iteration: 3, Log-Lik: -11458.503, Max-Change: 0.24005
Iteration: 4, Log-Lik: -11444.588, Max-Change: 0.11297
Iteration: 5, Log-Lik: -11440.296, Max-Change: 0.07114
Iteration: 6, Log-Lik: -11438.606, Max-Change: 0.05519
Iteration: 7, Log-Lik: -11437.501, Max-Change: 0.02367
Iteration: 8, Log-Lik: -11437.281, Max-Change: 0.01407
Iteration: 9, Log-Lik: -11437.192, Max-Change: 0.00843
Iteration: 10, Log-Lik: -11437.133, Max-Change: 0.00472
Iteration: 11, Log-Lik: -11437.115, Max-Change: 0.00276
Iteration: 12, Log-Lik: -11437.107, Max-Change: 0.00167
Iteration: 13, Log-Lik: -11437.100, Max-Change: 0.00107
Iteration: 14, Log-Lik: -11437.097, Max-Change: 0.00083
Iteration: 15, Log-Lik: -11437.095, Max-Change: 0.00075
Iteration: 16, Log-Lik: -11437.087, Max-Change: 0.00069
Iteration: 17, Log-Lik: -11437.087, Max-Change: 0.00048
Iteration: 18, Log-Lik: -11437.087, Max-Change: 0.00036
Iteration: 19, Log-Lik: -11437.087, Max-Change: 0.00043
Iteration: 20, Log-Lik: -11437.086, Max-Change: 0.00045
Iteration: 21, Log-Lik: -11437.086, Max-Change: 0.00061
Iteration: 22, Log-Lik: -11437.086, Max-Change: 0.00022
Iteration: 23, Log-Lik: -11437.086, Max-Change: 0.00031
Iteration: 24, Log-Lik: -11437.086, Max-Change: 0.00034
Iteration: 25, Log-Lik: -11437.086, Max-Change: 0.00021
Iteration: 26, Log-Lik: -11437.086, Max-Change: 0.00022
Iteration: 27, Log-Lik: -11437.086, Max-Change: 0.00029
Iteration: 28, Log-Lik: -11437.086, Max-Change: 0.00013
Iteration: 29, Log-Lik: -11437.086, Max-Change: 0.00017
Iteration: 30, Log-Lik: -11437.086, Max-Change: 0.00019
Iteration: 31, Log-Lik: -11437.086, Max-Change: 0.00010
Iteration: 32, Log-Lik: -11437.086, Max-Change: 0.00012
Iteration: 33, Log-Lik: -11437.086, Max-Change: 0.00015
Iteration: 34, Log-Lik: -11437.086, Max-Change: 0.00007

## 
## Step 5: Fit without DIF items, conservative threshold

## 
Iteration: 1, Log-Lik: -11709.945, Max-Change: 0.64135
Iteration: 2, Log-Lik: -11493.746, Max-Change: 0.29276
Iteration: 3, Log-Lik: -11458.503, Max-Change: 0.24005
Iteration: 4, Log-Lik: -11444.588, Max-Change: 0.11297
Iteration: 5, Log-Lik: -11440.296, Max-Change: 0.07114
Iteration: 6, Log-Lik: -11438.606, Max-Change: 0.05519
Iteration: 7, Log-Lik: -11437.501, Max-Change: 0.02367
Iteration: 8, Log-Lik: -11437.281, Max-Change: 0.01407
Iteration: 9, Log-Lik: -11437.192, Max-Change: 0.00843
Iteration: 10, Log-Lik: -11437.133, Max-Change: 0.00472
Iteration: 11, Log-Lik: -11437.115, Max-Change: 0.00276
Iteration: 12, Log-Lik: -11437.107, Max-Change: 0.00167
Iteration: 13, Log-Lik: -11437.100, Max-Change: 0.00107
Iteration: 14, Log-Lik: -11437.097, Max-Change: 0.00083
Iteration: 15, Log-Lik: -11437.095, Max-Change: 0.00075
Iteration: 16, Log-Lik: -11437.087, Max-Change: 0.00069
Iteration: 17, Log-Lik: -11437.087, Max-Change: 0.00048
Iteration: 18, Log-Lik: -11437.087, Max-Change: 0.00036
Iteration: 19, Log-Lik: -11437.087, Max-Change: 0.00043
Iteration: 20, Log-Lik: -11437.086, Max-Change: 0.00045
Iteration: 21, Log-Lik: -11437.086, Max-Change: 0.00061
Iteration: 22, Log-Lik: -11437.086, Max-Change: 0.00022
Iteration: 23, Log-Lik: -11437.086, Max-Change: 0.00031
Iteration: 24, Log-Lik: -11437.086, Max-Change: 0.00034
Iteration: 25, Log-Lik: -11437.086, Max-Change: 0.00021
Iteration: 26, Log-Lik: -11437.086, Max-Change: 0.00022
Iteration: 27, Log-Lik: -11437.086, Max-Change: 0.00029
Iteration: 28, Log-Lik: -11437.086, Max-Change: 0.00013
Iteration: 29, Log-Lik: -11437.086, Max-Change: 0.00017
Iteration: 30, Log-Lik: -11437.086, Max-Change: 0.00019
Iteration: 31, Log-Lik: -11437.086, Max-Change: 0.00010
Iteration: 32, Log-Lik: -11437.086, Max-Change: 0.00012
Iteration: 33, Log-Lik: -11437.086, Max-Change: 0.00015
Iteration: 34, Log-Lik: -11437.086, Max-Change: 0.00007

## 
## Step 6: Fit with anchor items, liberal threshold

## 
Iteration: 1, Log-Lik: -11709.945, Max-Change: 0.53950
Iteration: 2, Log-Lik: -11462.959, Max-Change: 0.23412
Iteration: 3, Log-Lik: -11441.830, Max-Change: 0.10408
Iteration: 4, Log-Lik: -11439.093, Max-Change: 0.04927
Iteration: 5, Log-Lik: -11438.528, Max-Change: 0.02438
Iteration: 6, Log-Lik: -11438.331, Max-Change: 0.01260
Iteration: 7, Log-Lik: -11438.201, Max-Change: 0.00668
Iteration: 8, Log-Lik: -11438.094, Max-Change: 0.00604
Iteration: 9, Log-Lik: -11437.992, Max-Change: 0.00640
Iteration: 10, Log-Lik: -11437.630, Max-Change: 0.02013
Iteration: 11, Log-Lik: -11437.382, Max-Change: 0.00766
Iteration: 12, Log-Lik: -11437.289, Max-Change: 0.00729
Iteration: 13, Log-Lik: -11436.957, Max-Change: 0.01915
Iteration: 14, Log-Lik: -11436.731, Max-Change: 0.00636
Iteration: 15, Log-Lik: -11436.646, Max-Change: 0.00657
Iteration: 16, Log-Lik: -11436.341, Max-Change: 0.01829
Iteration: 17, Log-Lik: -11436.134, Max-Change: 0.00661
Iteration: 18, Log-Lik: -11436.056, Max-Change: 0.00657
Iteration: 19, Log-Lik: -11435.777, Max-Change: 0.01745
Iteration: 20, Log-Lik: -11435.587, Max-Change: 0.00617
Iteration: 21, Log-Lik: -11435.516, Max-Change: 0.00627
Iteration: 22, Log-Lik: -11435.259, Max-Change: 0.01671
Iteration: 23, Log-Lik: -11435.084, Max-Change: 0.00606
Iteration: 24, Log-Lik: -11435.018, Max-Change: 0.00610
Iteration: 25, Log-Lik: -11434.782, Max-Change: 0.01602
Iteration: 26, Log-Lik: -11434.621, Max-Change: 0.00582
Iteration: 27, Log-Lik: -11434.561, Max-Change: 0.00589
Iteration: 28, Log-Lik: -11434.342, Max-Change: 0.01536
Iteration: 29, Log-Lik: -11434.194, Max-Change: 0.00565
Iteration: 30, Log-Lik: -11434.138, Max-Change: 0.00571
Iteration: 31, Log-Lik: -11433.937, Max-Change: 0.01474
Iteration: 32, Log-Lik: -11433.800, Max-Change: 0.00545
Iteration: 33, Log-Lik: -11433.749, Max-Change: 0.00552
Iteration: 34, Log-Lik: -11433.562, Max-Change: 0.01417
Iteration: 35, Log-Lik: -11433.436, Max-Change: 0.00527
Iteration: 36, Log-Lik: -11433.388, Max-Change: 0.00535
Iteration: 37, Log-Lik: -11433.215, Max-Change: 0.01364
Iteration: 38, Log-Lik: -11433.099, Max-Change: 0.00510
Iteration: 39, Log-Lik: -11433.054, Max-Change: 0.00518
Iteration: 40, Log-Lik: -11432.894, Max-Change: 0.01314
Iteration: 41, Log-Lik: -11432.786, Max-Change: 0.00493
Iteration: 42, Log-Lik: -11432.745, Max-Change: 0.00502
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Iteration: 45, Log-Lik: -11432.457, Max-Change: 0.00486
Iteration: 46, Log-Lik: -11432.319, Max-Change: 0.01223
Iteration: 47, Log-Lik: -11432.226, Max-Change: 0.00462
Iteration: 48, Log-Lik: -11432.190, Max-Change: 0.00470
Iteration: 49, Log-Lik: -11432.061, Max-Change: 0.01182
Iteration: 50, Log-Lik: -11431.974, Max-Change: 0.00447
Iteration: 51, Log-Lik: -11431.941, Max-Change: 0.00456
Iteration: 52, Log-Lik: -11431.821, Max-Change: 0.01142
Iteration: 53, Log-Lik: -11431.740, Max-Change: 0.00433
Iteration: 54, Log-Lik: -11431.709, Max-Change: 0.00441
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Iteration: 56, Log-Lik: -11431.521, Max-Change: 0.00419
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Iteration: 61, Log-Lik: -11431.192, Max-Change: 0.01038
Iteration: 62, Log-Lik: -11431.126, Max-Change: 0.00393
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Iteration: 65, Log-Lik: -11430.947, Max-Change: 0.00380
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Iteration: 67, Log-Lik: -11430.837, Max-Change: 0.00977
Iteration: 68, Log-Lik: -11430.779, Max-Change: 0.00368
Iteration: 69, Log-Lik: -11430.757, Max-Change: 0.00377
Iteration: 70, Log-Lik: -11430.676, Max-Change: 0.00948
Iteration: 71, Log-Lik: -11430.621, Max-Change: 0.00357
Iteration: 72, Log-Lik: -11430.600, Max-Change: 0.00365
Iteration: 73, Log-Lik: -11430.525, Max-Change: 0.00921
Iteration: 74, Log-Lik: -11430.473, Max-Change: 0.00346
Iteration: 75, Log-Lik: -11430.454, Max-Change: 0.00354
Iteration: 76, Log-Lik: -11430.382, Max-Change: 0.00895
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Iteration: 78, Log-Lik: -11430.315, Max-Change: 0.00343
Iteration: 79, Log-Lik: -11430.248, Max-Change: 0.00872
Iteration: 80, Log-Lik: -11430.202, Max-Change: 0.00324
Iteration: 81, Log-Lik: -11430.185, Max-Change: 0.00332
Iteration: 82, Log-Lik: -11430.122, Max-Change: 0.00848
Iteration: 83, Log-Lik: -11430.079, Max-Change: 0.00314
Iteration: 84, Log-Lik: -11430.062, Max-Change: 0.00321
Iteration: 85, Log-Lik: -11430.003, Max-Change: 0.00825
Iteration: 86, Log-Lik: -11429.962, Max-Change: 0.00304
Iteration: 87, Log-Lik: -11429.946, Max-Change: 0.00312
Iteration: 88, Log-Lik: -11429.890, Max-Change: 0.00804
Iteration: 89, Log-Lik: -11429.851, Max-Change: 0.00295
Iteration: 90, Log-Lik: -11429.837, Max-Change: 0.00302
Iteration: 91, Log-Lik: -11429.784, Max-Change: 0.00783
Iteration: 92, Log-Lik: -11429.747, Max-Change: 0.00286
Iteration: 93, Log-Lik: -11429.733, Max-Change: 0.00293
Iteration: 94, Log-Lik: -11429.683, Max-Change: 0.00764
Iteration: 95, Log-Lik: -11429.648, Max-Change: 0.00277
Iteration: 96, Log-Lik: -11429.635, Max-Change: 0.00284
Iteration: 97, Log-Lik: -11429.588, Max-Change: 0.00745
Iteration: 98, Log-Lik: -11429.554, Max-Change: 0.00268
Iteration: 99, Log-Lik: -11429.542, Max-Change: 0.00275
Iteration: 100, Log-Lik: -11429.497, Max-Change: 0.00728
Iteration: 101, Log-Lik: -11429.465, Max-Change: 0.00260
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## 
## Step 7: Fit with anchor items, conservative threshold

## 
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## 
## Step 8: Get scores

## $scores
## $scores$original
##                   F1     SE_F1
##    [1,] -0.119788822 0.3670298
##    [2,]  0.235142472 0.3982720
##    [3,]  0.573613062 0.4344155
##    [4,]  0.735956027 0.4526857
##    [5,]  1.237616162 0.5083121
##    [6,] -0.026565524 0.3742960
##    [7,]  0.424283987 0.4179944
##    [8,] -0.732676204 0.3429991
##    [9,] -0.204114369 0.3611555
##   [10,]  0.859851975 0.4666922
##   [11,] -0.972208784 0.3471276
##   [12,] -1.045921602 0.3500715
##   [13,] -0.206881519 0.3609748
##   [14,] -0.154051933 0.3645591
##   [15,] -0.373441849 0.3516163
##   [16,]  0.990475554 0.4813457
##   [17,]  0.406751189 0.4161066
##   [18,]  0.560705465 0.4329766
##   [19,] -0.750774625 0.3430245
##   [20,] -0.958803823 0.3466775
##   [21,]  1.746234902 0.5591073
##   [22,]  0.174488560 0.3923142
##   [23,] -0.217474468 0.3602901
##   [24,]  1.012247365 0.4837672
##   [25,] -0.763386473 0.3430695
##   [26,] -0.976577554 0.3472800
##   [27,] -0.744947997 0.3430113
##   [28,]  0.090964580 0.3844787
##   [29,] -0.342899683 0.3530992
##   [30,] -0.365291532 0.3520014
##   [31,]  0.693216937 0.4478550
##   [32,] -0.627607560 0.3437520
##   [33,] -1.085779886 0.3519935
##   [34,]  0.324649773 0.4074147
##   [35,]  0.693216937 0.4478550
##   [36,]  0.448801323 0.4206508
##   [37,]  0.079939591 0.3834795
##   [38,] -0.572582465 0.3447467
##   [39,]  0.299564207 0.4048141
##   [40,] -0.786146575 0.3432076
##   [41,] -0.404686026 0.3502132
##   [42,]  0.874153953 0.4683049
##   [43,] -1.427695317 0.3778515
##   [44,] -0.704283332 0.3430518
##   [45,]  1.078705956 0.4911104
##   [46,] -1.408691205 0.3759852
##   [47,]  0.336511031 0.4086540
##   [48,]  1.179128339 0.5020454
##   [49,]  0.406751189 0.4161066
##   [50,]  0.111934763 0.3864027
##   [51,]  2.571997950 0.6312275
##   [52,] -0.167168605 0.3636432
##   [53,] -0.118670475 0.3671123
##   [54,]  0.856203256 0.4662806
##   [55,]  1.179128339 0.5020454
##   [56,] -1.226391295 0.3606164
##   [57,] -0.144607431 0.3652289
##   [58,] -0.199051218 0.3614883
##   [59,]  1.288904294 0.5137399
##   [60,] -0.226441676 0.3597196
##   [61,]  0.095368777 0.3848803
##   [62,]  0.537696269 0.4304192
##   [63,] -0.385185903 0.3510753
##   [64,]  1.116616465 0.4952629
##   [65,]  0.496474279 0.4258652
##   [66,] -0.430459704 0.3491443
##   [67,]  0.031635458 0.3792059
##   [68,]  0.914884461 0.4728882
##   [69,] -1.264502151 0.3634433
##   [70,]  0.541304896 0.4308196
##   [71,] -1.126799027 0.3542132
##   [72,]  1.512466558 0.5366045
##   [73,]  0.362613926 0.4114016
##   [74,]  0.094933338 0.3848405
##   [75,] -0.857252902 0.3441156
##   [76,]  0.815470533 0.4616799
##   [77,]  1.310697531 0.5160263
##   [78,]  0.600986447 0.4374760
##   [79,]  0.201502440 0.3949418
##   [80,] -0.313140960 0.3546477
##   [81,]  0.311258478 0.4060229
##   [82,] -0.472773429 0.3475666
##   [83,] -1.156538860 0.3559753
##   [84,] -0.800511828 0.3433328
##   [85,] -0.166972560 0.3636568
##   [86,]  0.722318910 0.4511436
##   [87,]  0.100250642 0.3853270
##   [88,]  1.107739990 0.4942932
##   [89,]  0.622829977 0.4399259
##   [90,]  0.582763215 0.4354373
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##  [907,] -0.644941142 0.3435232
##  [908,]  0.757766480 0.4551530
##  [909,] -0.082009010 0.3698814
##  [910,]  0.003103605 0.3767650
##  [911,] -0.982767735 0.3475007
##  [912,] -1.110906534 0.3533242
##  [913,]  0.471945740 0.4231746
##  [914,]  0.415521474 0.4170496
##  [915,] -0.501692906 0.3466175
##  [916,]  0.643424343 0.4422411
##  [917,] -0.577693640 0.3446373
##  [918,]  0.134759990 0.3885306
##  [919,]  1.214150745 0.5058075
##  [920,] -0.060628953 0.3715521
##  [921,]  0.253369612 0.4001019
##  [922,] -0.611846788 0.3439954
##  [923,]  0.693216937 0.4478550
##  [924,] -0.429474147 0.3491837
##  [925,] -0.463765525 0.3478838
##  [926,] -1.352375631 0.3707434
##  [927,]  0.116814391 0.3868547
##  [928,] -0.760627800 0.3430577
##  [929,]  0.079939591 0.3834795
##  [930,] -0.649438912 0.3434705
##  [931,] -1.684764636 0.4076720
##  [932,]  0.194033652 0.3942111
##  [933,] -0.309249791 0.3548576
##  [934,]  0.055880820 0.3813293
##  [935,] -1.609628939 0.3981094
##  [936,] -0.027492208 0.3742201
##  [937,]  0.028540011 0.3789380
##  [938,]  0.549160464 0.4316922
##  [939,] -0.482524487 0.3472347
##  [940,] -1.529441237 0.3886584
##  [941,] -0.234024491 0.3592437
##  [942,]  1.508618965 0.5362223
##  [943,]  0.609652096 0.4384472
##  [944,] -0.420294109 0.3495562
##  [945,] -1.588287070 0.3955162
##  [946,] -0.046933319 0.3726434
##  [947,] -0.141152402 0.3654761
##  [948,]  0.950845822 0.4769206
##  [949,]  1.706868337 0.5554140
##  [950,] -0.289964876 0.3559230
##  [951,] -1.152500185 0.3557285
##  [952,]  0.891462779 0.4702544
##  [953,] -0.284243870 0.3562470
##  [954,]  0.630130786 0.4407461
##  [955,] -0.931355330 0.3458374
##  [956,] -0.664778207 0.3433117
##  [957,]  0.311258478 0.4060229
##  [958,]  0.738803644 0.4530078
##  [959,]  0.073735400 0.3829210
##  [960,] -1.114948918 0.3535468
##  [961,] -0.104346880 0.3681795
##  [962,] -0.021604375 0.3747038
##  [963,]  0.457075306 0.4215513
##  [964,]  0.460415354 0.4219154
##  [965,] -0.757678833 0.3430463
##  [966,]  0.347183811 0.4097741
##  [967,]  0.003103605 0.3767650
##  [968,]  0.216542495 0.3964229
##  [969,] -0.726926806 0.3430007
##  [970,] -0.654987982 0.3434093
##  [971,]  0.609652096 0.4384472
##  [972,] -0.150651549 0.3647992
##  [973,]  0.097217693 0.3850493
##  [974,]  0.794213264 0.4592762
##  [975,] -1.887743016 0.4365936
##  [976,] -0.803917482 0.3433667
##  [977,] -0.118670475 0.3671123
##  [978,] -1.444397438 0.3795318
##  [979,]  1.183358362 0.5025013
##  [980,] -0.755672181 0.3430393
##  [981,] -0.289599860 0.3559435
##  [982,]  0.769194336 0.4564459
##  [983,]  0.609652096 0.4384472
##  [984,]  0.088289036 0.3842355
##  [985,] -0.302879577 0.3552049
##  [986,] -0.618213278 0.3438930
##  [987,] -0.322655507 0.3541417
##  [988,]  0.159178368 0.3908444
##  [989,]  1.092669542 0.4926432
##  [990,] -1.245454175 0.3620045
##  [991,]  0.549697475 0.4317519
##  [992,] -1.274125553 0.3641898
##  [993,] -0.054790629 0.3720154
##  [994,]  0.507978514 0.4271322
##  [995,]  0.537696269 0.4304192
##  [996,]  2.113748965 0.5920662
##  [997,] -0.732036337 0.3429990
##  [998,] -0.209526284 0.3608027
##  [999,] -0.030535438 0.3739712
## [1000,] -0.451094564 0.3483471
## [1001,]  0.311258478 0.4060229
## [1002,] -0.341888725 0.3531502
## [1003,]  0.086081207 0.3840351
## [1004,]  1.508618965 0.5362223
## [1005,]  2.113748965 0.5920662
## [1006,]  0.046927634 0.3805400
## [1007,]  0.481877064 0.4242621
## [1008,]  0.481877064 0.4242621
## [1009,] -0.454003839 0.3482390
## [1010,]  1.037088927 0.4865209
## [1011,]  1.508618965 0.5362223
## [1012,]  0.670606609 0.4453033
## [1013,] -1.648814340 0.4030138
## [1014,] -0.673266707 0.3432376
## [1015,] -0.495687186 0.3468059
## [1016,] -0.619508395 0.3438728
## [1017,]  0.609652096 0.4384472
## [1018,]  0.073735400 0.3829210
## [1019,]  0.539732105 0.4306451
## [1020,]  0.231027250 0.3978613
## [1021,]  0.158943517 0.3908220
## [1022,] -0.648532697 0.3434809
## [1023,]  1.067086218 0.4898321
## [1024,] -0.852689542 0.3440356
## [1025,] -0.083649181 0.3697549
## [1026,] -1.608270993 0.3979428
## [1027,]  1.427164102 0.5280367
## [1028,] -0.348310400 0.3528286
## [1029,]  0.350309851 0.4101030
## [1030,] -1.329745380 0.3687601
## [1031,] -1.195464275 0.3584749
## [1032,]  0.090538712 0.3844400
## [1033,]  0.512958568 0.4276817
## [1034,] -0.368584931 0.3518448
## [1035,] -0.473279361 0.3475491
## [1036,]  0.167119264 0.3916050
## [1037,] -0.215205560 0.3604357
## [1038,]  0.041983108 0.3801067
## [1039,]  0.318883675 0.4068145
## [1040,]  0.597827181 0.4371222
## [1041,] -0.704283332 0.3430518
## [1042,] -0.875947174 0.3444750
## [1043,]  0.023723143 0.3785226
## [1044,] -0.110018572 0.3677546
## [1045,] -0.277040826 0.3566600
## [1046,]  0.199179605 0.3947142
## [1047,]  0.692491220 0.4477730
## [1048,] -0.417443117 0.3496740
## [1049,] -0.606170270 0.3440912
## [1050,] -1.144572402 0.3552508
## [1051,] -0.807805297 0.3434076
## [1052,]  0.799428063 0.4598660
## [1053,] -0.495858749 0.3468004
## [1054,] -0.473279361 0.3475491
## [1055,]  0.402396771 0.4156393
## [1056,] -0.083076494 0.3697990
## [1057,]  0.098642592 0.3851797
## [1058,] -0.255013389 0.3579582
## [1059,] -0.244829019 0.3585761
## [1060,] -0.394226286 0.3506699
## [1061,] -1.086602352 0.3520356
## [1062,]  0.083852984 0.3838332
## [1063,]  0.252414481 0.4000055
## [1064,] -0.498064544 0.3467308
## [1065,] -0.500193792 0.3466641
## [1066,] -0.162276926 0.3639828
## [1067,] -0.627607560 0.3437520
## [1068,] -0.862757714 0.3442162
## [1069,]  0.284321086 0.4032478
## [1070,] -0.275986349 0.3567209
## [1071,]  0.549697475 0.4317519
## [1072,] -1.646578704 0.4027290
## [1073,] -0.721477211 0.3430064
## [1074,] -0.606681778 0.3440824
## [1075,]  0.990475554 0.4813457
## [1076,] -0.141152402 0.3654761
## [1077,] -0.343078531 0.3530902
## [1078,]  0.158943517 0.3908220
## [1079,]  0.068090949 0.3824153
## [1080,] -0.133751287 0.3660094
## [1081,] -0.166972560 0.3636568
## [1082,]  2.113748965 0.5920662
## [1083,] -0.562062872 0.3449828
## [1084,]  0.018770540 0.3780974
## [1085,]  0.055880820 0.3813293
## [1086,] -0.771633007 0.3431110
## [1087,]  0.360714423 0.4112007
## [1088,] -0.445367595 0.3485631
## [1089,] -0.320831810 0.3542379
## [1090,]  0.880316573 0.4689993
## [1091,] -0.666295184 0.3432977
## [1092,]  0.196112226 0.3944141
## [1093,]  0.094743247 0.3848232
## [1094,] -0.708124794 0.3430381
## [1095,] -1.920171194 0.4415872
## [1096,] -0.903206537 0.3450896
## [1097,]  0.819047580 0.4620843
## [1098,] -1.112311643 0.3534013
## [1099,]  0.637538655 0.4415789
## [1100,]  0.609652096 0.4384472
## [1101,] -0.723023409 0.3430044
## [1102,] -0.273283485 0.3568777
## [1103,] -0.647468339 0.3434932
## [1104,]  0.321382069 0.4070744
## [1105,] -1.151719643 0.3556810
## [1106,] -0.450660719 0.3483633
## [1107,]  1.163628947 0.5003716
## [1108,]  1.097005069 0.4931183
## [1109,]  0.144963779 0.3894929
## [1110,] -1.044833457 0.3500223
## [1111,] -0.172624267 0.3632673
## [1112,] -0.018710856 0.3749426
## [1113,] -0.387672777 0.3509628
## [1114,]  0.406751189 0.4161066
## [1115,]  1.067301163 0.4898558
## [1116,]  0.917676235 0.4732017
## [1117,]  0.242326369 0.3989911
## [1118,]  1.845426522 0.5682556
## [1119,] -0.452313865 0.3483017
## [1120,] -0.938688015 0.3460510
## [1121,]  2.113748965 0.5920662
## [1122,] -0.303368910 0.3551781
## [1123,]  1.388993401 0.5241398
## [1124,]  0.159383646 0.3908641
## [1125,] -0.148640512 0.3649418
## [1126,] -0.104346880 0.3681795
## [1127,]  1.143489269 0.4981889
## [1128,]  1.223445608 0.5068012
## [1129,] -0.766129950 0.3430822
## [1130,]  0.163029877 0.3912128
## [1131,] -0.644961030 0.3435229
## [1132,] -0.473279361 0.3475491
## [1133,] -1.864016600 0.4330002
## [1134,] -0.210004752 0.3607717
## [1135,] -1.008022153 0.3484589
## [1136,]  0.406751189 0.4161066
## [1137,]  2.571997950 0.6312275
## [1138,] -0.284242313 0.3562470
## [1139,] -0.471782767 0.3476010
## [1140,] -0.907619800 0.3451992
## [1141,] -0.572675218 0.3447447
## [1142,] -0.030132453 0.3740041
## [1143,]  0.167119264 0.3916050
## [1144,]  0.174551761 0.3923203
## [1145,]  0.490995349 0.4252629
## [1146,]  0.419614473 0.4174907
## [1147,]  1.350994175 0.5202221
## [1148,]  0.990475554 0.4813457
## [1149,]  0.079595756 0.3834485
## [1150,] -0.115166538 0.3673716
## [1151,] -1.026230902 0.3492075
## [1152,]  0.130828328 0.3881616
## [1153,] -0.775929504 0.3431365
## [1154,] -0.921972476 0.3455753
## [1155,]  0.124474032 0.3875674
## [1156,]  0.914884461 0.4728882
## [1157,]  0.299564207 0.4048141
## [1158,]  0.382887707 0.4135539
## [1159,]  1.704537825 0.5551942
## [1160,] -0.412541142 0.3498789
## [1161,]  0.856203256 0.4662806
## [1162,]  1.179128339 0.5020454
## [1163,]  0.334301877 0.4084227
## [1164,]  0.864911266 0.4672629
## [1165,] -0.526534102 0.3458876
## [1166,]  0.282293423 0.4030402
## [1167,] -0.900577188 0.3450256
## [1168,] -1.293702536 0.3657489
## [1169,] -0.249586347 0.3582861
## [1170,]  0.627708731 0.4404739
## [1171,]  0.313387939 0.4062437
## [1172,]  0.609652096 0.4384472
## [1173,]  1.195843145 0.5038444
## [1174,] -0.937317953 0.3460105
## [1175,]  0.012218423 0.3775378
## [1176,]  0.674111100 0.4456986
## [1177,] -0.993827623 0.3479088
## [1178,]  0.471945740 0.4231746
## [1179,]  0.609087039 0.4383838
## [1180,] -0.442084962 0.3486887
## [1181,] -0.264498229 0.3573928
## [1182,] -0.496615901 0.3467765
## [1183,] -0.819721261 0.3435461
## [1184,] -0.135230005 0.3659024
## [1185,]  1.424057824 0.5277210
## [1186,]  0.201297757 0.3949217
## [1187,]  0.643446596 0.4422436
## [1188,]  0.049747564 0.3807880
## [1189,]  0.207925316 0.3955728
## [1190,] -1.604870236 0.3975264
## [1191,]  0.415521474 0.4170496
## [1192,] -0.180198114 0.3627503
## [1193,]  0.541304896 0.4308196
## [1194,] -0.239660428 0.3588939
## [1195,] -0.939774036 0.3460834
## [1196,] -1.608270993 0.3979428
## [1197,] -0.084043063 0.3697245
## [1198,] -1.465161299 0.3816726
## [1199,] -1.443954954 0.3794868
## [1200,] -1.131639047 0.3544912
## [1201,] -1.041188799 0.3498586
## [1202,] -1.499853054 0.3853762
## [1203,] -1.140408945 0.3550037
## [1204,] -0.806971621 0.3433986
## [1205,] -0.276206120 0.3567082
## [1206,] -1.202750173 0.3589670
## [1207,]  1.061979312 0.4892695
## [1208,] -0.458610089 0.3480699
## [1209,] -0.284242313 0.3562470
## [1210,]  2.406223499 0.6171067
## [1211,] -0.622807499 0.3438225
## [1212,] -0.597287836 0.3442499
## [1213,] -0.413348293 0.3498449
## [1214,]  1.576249549 0.5428840
## [1215,] -1.182318005 0.3576063
## [1216,]  0.381468708 0.4134028
## [1217,] -0.478838984 0.3473588
## [1218,]  0.269424539 0.4017278
## [1219,]  0.769194336 0.4564459
## [1220,]  0.511527044 0.4275237
## [1221,] -0.746056106 0.3430134
## [1222,]  1.423185812 0.5276323
## [1223,] -0.084861188 0.3696615
## [1224,]  0.160211663 0.3909432
## [1225,] -0.083649181 0.3697549
## [1226,] -1.693294021 0.4087991
## [1227,] -0.852689542 0.3440356
## [1228,] -0.672927263 0.3432404
## [1229,]  1.738575872 0.5583916
## [1230,]  1.179128339 0.5020454
## [1231,] -1.499853054 0.3853762
## [1232,] -0.673266707 0.3432376
## [1233,] -0.297052714 0.3555266
## [1234,]  0.914884461 0.4728882
## [1235,] -2.193610396 0.4868621
## [1236,] -1.126730361 0.3542093
## [1237,] -1.233461814 0.3611252
## [1238,]  1.129397337 0.4966564
## [1239,]  0.495195684 0.4257246
## 
## $scores$noDIF_liberal
##                   F1     SE_F1
##    [1,] -0.119788822 0.3670298
##    [2,]  0.235142472 0.3982720
##    [3,]  0.573613062 0.4344155
##    [4,]  0.735956027 0.4526857
##    [5,]  1.237616162 0.5083121
##    [6,] -0.026565524 0.3742960
##    [7,]  0.424283987 0.4179944
##    [8,] -0.732676204 0.3429991
##    [9,] -0.204114369 0.3611555
##   [10,]  0.859851975 0.4666922
##   [11,] -0.972208784 0.3471276
##   [12,] -1.045921602 0.3500715
##   [13,] -0.206881519 0.3609748
##   [14,] -0.154051933 0.3645591
##   [15,] -0.373441849 0.3516163
##   [16,]  0.990475554 0.4813457
##   [17,]  0.406751189 0.4161066
##   [18,]  0.560705465 0.4329766
##   [19,] -0.750774625 0.3430245
##   [20,] -0.958803823 0.3466775
##   [21,]  1.746234902 0.5591073
##   [22,]  0.174488560 0.3923142
##   [23,] -0.217474468 0.3602901
##   [24,]  1.012247365 0.4837672
##   [25,] -0.763386473 0.3430695
##   [26,] -0.976577554 0.3472800
##   [27,] -0.744947997 0.3430113
##   [28,]  0.090964580 0.3844787
##   [29,] -0.342899683 0.3530992
##   [30,] -0.365291532 0.3520014
##   [31,]  0.693216937 0.4478550
##   [32,] -0.627607560 0.3437520
##   [33,] -1.085779886 0.3519935
##   [34,]  0.324649773 0.4074147
##   [35,]  0.693216937 0.4478550
##   [36,]  0.448801323 0.4206508
##   [37,]  0.079939591 0.3834795
##   [38,] -0.572582465 0.3447467
##   [39,]  0.299564207 0.4048141
##   [40,] -0.786146575 0.3432076
##   [41,] -0.404686026 0.3502132
##   [42,]  0.874153953 0.4683049
##   [43,] -1.427695317 0.3778515
##   [44,] -0.704283332 0.3430518
##   [45,]  1.078705956 0.4911104
##   [46,] -1.408691205 0.3759852
##   [47,]  0.336511031 0.4086540
##   [48,]  1.179128339 0.5020454
##   [49,]  0.406751189 0.4161066
##   [50,]  0.111934763 0.3864027
##   [51,]  2.571997950 0.6312275
##   [52,] -0.167168605 0.3636432
##   [53,] -0.118670475 0.3671123
##   [54,]  0.856203256 0.4662806
##   [55,]  1.179128339 0.5020454
##   [56,] -1.226391295 0.3606164
##   [57,] -0.144607431 0.3652289
##   [58,] -0.199051218 0.3614883
##   [59,]  1.288904294 0.5137399
##   [60,] -0.226441676 0.3597196
##   [61,]  0.095368777 0.3848803
##   [62,]  0.537696269 0.4304192
##   [63,] -0.385185903 0.3510753
##   [64,]  1.116616465 0.4952629
##   [65,]  0.496474279 0.4258652
##   [66,] -0.430459704 0.3491443
##   [67,]  0.031635458 0.3792059
##   [68,]  0.914884461 0.4728882
##   [69,] -1.264502151 0.3634433
##   [70,]  0.541304896 0.4308196
##   [71,] -1.126799027 0.3542132
##   [72,]  1.512466558 0.5366045
##   [73,]  0.362613926 0.4114016
##   [74,]  0.094933338 0.3848405
##   [75,] -0.857252902 0.3441156
##   [76,]  0.815470533 0.4616799
##   [77,]  1.310697531 0.5160263
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##  [894,]  1.706868337 0.5554140
##  [895,] -0.376554346 0.3514713
##  [896,]  0.481877064 0.4242621
##  [897,]  0.134759990 0.3885306
##  [898,]  0.073735400 0.3829210
##  [899,] -1.380441943 0.3733015
##  [900,] -0.567591293 0.3448569
##  [901,] -0.754004346 0.3430338
##  [902,]  0.663954803 0.4445533
##  [903,]  0.637538655 0.4415789
##  [904,]  0.621077321 0.4397291
##  [905,] -0.899219423 0.3449930
##  [906,] -0.473279361 0.3475491
##  [907,] -0.644941142 0.3435232
##  [908,]  0.757766480 0.4551530
##  [909,] -0.082009010 0.3698814
##  [910,]  0.003103605 0.3767650
##  [911,] -0.982767735 0.3475007
##  [912,] -1.110906534 0.3533242
##  [913,]  0.471945740 0.4231746
##  [914,]  0.415521474 0.4170496
##  [915,] -0.501692906 0.3466175
##  [916,]  0.643424343 0.4422411
##  [917,] -0.577693640 0.3446373
##  [918,]  0.134759990 0.3885306
##  [919,]  1.214150745 0.5058075
##  [920,] -0.060628953 0.3715521
##  [921,]  0.253369612 0.4001019
##  [922,] -0.611846788 0.3439954
##  [923,]  0.693216937 0.4478550
##  [924,] -0.429474147 0.3491837
##  [925,] -0.463765525 0.3478838
##  [926,] -1.352375631 0.3707434
##  [927,]  0.116814391 0.3868547
##  [928,] -0.760627800 0.3430577
##  [929,]  0.079939591 0.3834795
##  [930,] -0.649438912 0.3434705
##  [931,] -1.684764636 0.4076720
##  [932,]  0.194033652 0.3942111
##  [933,] -0.309249791 0.3548576
##  [934,]  0.055880820 0.3813293
##  [935,] -1.609628939 0.3981094
##  [936,] -0.027492208 0.3742201
##  [937,]  0.028540011 0.3789380
##  [938,]  0.549160464 0.4316922
##  [939,] -0.482524487 0.3472347
##  [940,] -1.529441237 0.3886584
##  [941,] -0.234024491 0.3592437
##  [942,]  1.508618965 0.5362223
##  [943,]  0.609652096 0.4384472
##  [944,] -0.420294109 0.3495562
##  [945,] -1.588287070 0.3955162
##  [946,] -0.046933319 0.3726434
##  [947,] -0.141152402 0.3654761
##  [948,]  0.950845822 0.4769206
##  [949,]  1.706868337 0.5554140
##  [950,] -0.289964876 0.3559230
##  [951,] -1.152500185 0.3557285
##  [952,]  0.891462779 0.4702544
##  [953,] -0.284243870 0.3562470
##  [954,]  0.630130786 0.4407461
##  [955,] -0.931355330 0.3458374
##  [956,] -0.664778207 0.3433117
##  [957,]  0.311258478 0.4060229
##  [958,]  0.738803644 0.4530078
##  [959,]  0.073735400 0.3829210
##  [960,] -1.114948918 0.3535468
##  [961,] -0.104346880 0.3681795
##  [962,] -0.021604375 0.3747038
##  [963,]  0.457075306 0.4215513
##  [964,]  0.460415354 0.4219154
##  [965,] -0.757678833 0.3430463
##  [966,]  0.347183811 0.4097741
##  [967,]  0.003103605 0.3767650
##  [968,]  0.216542495 0.3964229
##  [969,] -0.726926806 0.3430007
##  [970,] -0.654987982 0.3434093
##  [971,]  0.609652096 0.4384472
##  [972,] -0.150651549 0.3647992
##  [973,]  0.097217693 0.3850493
##  [974,]  0.794213264 0.4592762
##  [975,] -1.887743016 0.4365936
##  [976,] -0.803917482 0.3433667
##  [977,] -0.118670475 0.3671123
##  [978,] -1.444397438 0.3795318
##  [979,]  1.183358362 0.5025013
##  [980,] -0.755672181 0.3430393
##  [981,] -0.289599860 0.3559435
##  [982,]  0.769194336 0.4564459
##  [983,]  0.609652096 0.4384472
##  [984,]  0.088289036 0.3842355
##  [985,] -0.302879577 0.3552049
##  [986,] -0.618213278 0.3438930
##  [987,] -0.322655507 0.3541417
##  [988,]  0.159178368 0.3908444
##  [989,]  1.092669542 0.4926432
##  [990,] -1.245454175 0.3620045
##  [991,]  0.549697475 0.4317519
##  [992,] -1.274125553 0.3641898
##  [993,] -0.054790629 0.3720154
##  [994,]  0.507978514 0.4271322
##  [995,]  0.537696269 0.4304192
##  [996,]  2.113748965 0.5920662
##  [997,] -0.732036337 0.3429990
##  [998,] -0.209526284 0.3608027
##  [999,] -0.030535438 0.3739712
## [1000,] -0.451094564 0.3483471
## [1001,]  0.311258478 0.4060229
## [1002,] -0.341888725 0.3531502
## [1003,]  0.086081207 0.3840351
## [1004,]  1.508618965 0.5362223
## [1005,]  2.113748965 0.5920662
## [1006,]  0.046927634 0.3805400
## [1007,]  0.481877064 0.4242621
## [1008,]  0.481877064 0.4242621
## [1009,] -0.454003839 0.3482390
## [1010,]  1.037088927 0.4865209
## [1011,]  1.508618965 0.5362223
## [1012,]  0.670606609 0.4453033
## [1013,] -1.648814340 0.4030138
## [1014,] -0.673266707 0.3432376
## [1015,] -0.495687186 0.3468059
## [1016,] -0.619508395 0.3438728
## [1017,]  0.609652096 0.4384472
## [1018,]  0.073735400 0.3829210
## [1019,]  0.539732105 0.4306451
## [1020,]  0.231027250 0.3978613
## [1021,]  0.158943517 0.3908220
## [1022,] -0.648532697 0.3434809
## [1023,]  1.067086218 0.4898321
## [1024,] -0.852689542 0.3440356
## [1025,] -0.083649181 0.3697549
## [1026,] -1.608270993 0.3979428
## [1027,]  1.427164102 0.5280367
## [1028,] -0.348310400 0.3528286
## [1029,]  0.350309851 0.4101030
## [1030,] -1.329745380 0.3687601
## [1031,] -1.195464275 0.3584749
## [1032,]  0.090538712 0.3844400
## [1033,]  0.512958568 0.4276817
## [1034,] -0.368584931 0.3518448
## [1035,] -0.473279361 0.3475491
## [1036,]  0.167119264 0.3916050
## [1037,] -0.215205560 0.3604357
## [1038,]  0.041983108 0.3801067
## [1039,]  0.318883675 0.4068145
## [1040,]  0.597827181 0.4371222
## [1041,] -0.704283332 0.3430518
## [1042,] -0.875947174 0.3444750
## [1043,]  0.023723143 0.3785226
## [1044,] -0.110018572 0.3677546
## [1045,] -0.277040826 0.3566600
## [1046,]  0.199179605 0.3947142
## [1047,]  0.692491220 0.4477730
## [1048,] -0.417443117 0.3496740
## [1049,] -0.606170270 0.3440912
## [1050,] -1.144572402 0.3552508
## [1051,] -0.807805297 0.3434076
## [1052,]  0.799428063 0.4598660
## [1053,] -0.495858749 0.3468004
## [1054,] -0.473279361 0.3475491
## [1055,]  0.402396771 0.4156393
## [1056,] -0.083076494 0.3697990
## [1057,]  0.098642592 0.3851797
## [1058,] -0.255013389 0.3579582
## [1059,] -0.244829019 0.3585761
## [1060,] -0.394226286 0.3506699
## [1061,] -1.086602352 0.3520356
## [1062,]  0.083852984 0.3838332
## [1063,]  0.252414481 0.4000055
## [1064,] -0.498064544 0.3467308
## [1065,] -0.500193792 0.3466641
## [1066,] -0.162276926 0.3639828
## [1067,] -0.627607560 0.3437520
## [1068,] -0.862757714 0.3442162
## [1069,]  0.284321086 0.4032478
## [1070,] -0.275986349 0.3567209
## [1071,]  0.549697475 0.4317519
## [1072,] -1.646578704 0.4027290
## [1073,] -0.721477211 0.3430064
## [1074,] -0.606681778 0.3440824
## [1075,]  0.990475554 0.4813457
## [1076,] -0.141152402 0.3654761
## [1077,] -0.343078531 0.3530902
## [1078,]  0.158943517 0.3908220
## [1079,]  0.068090949 0.3824153
## [1080,] -0.133751287 0.3660094
## [1081,] -0.166972560 0.3636568
## [1082,]  2.113748965 0.5920662
## [1083,] -0.562062872 0.3449828
## [1084,]  0.018770540 0.3780974
## [1085,]  0.055880820 0.3813293
## [1086,] -0.771633007 0.3431110
## [1087,]  0.360714423 0.4112007
## [1088,] -0.445367595 0.3485631
## [1089,] -0.320831810 0.3542379
## [1090,]  0.880316573 0.4689993
## [1091,] -0.666295184 0.3432977
## [1092,]  0.196112226 0.3944141
## [1093,]  0.094743247 0.3848232
## [1094,] -0.708124794 0.3430381
## [1095,] -1.920171194 0.4415872
## [1096,] -0.903206537 0.3450896
## [1097,]  0.819047580 0.4620843
## [1098,] -1.112311643 0.3534013
## [1099,]  0.637538655 0.4415789
## [1100,]  0.609652096 0.4384472
## [1101,] -0.723023409 0.3430044
## [1102,] -0.273283485 0.3568777
## [1103,] -0.647468339 0.3434932
## [1104,]  0.321382069 0.4070744
## [1105,] -1.151719643 0.3556810
## [1106,] -0.450660719 0.3483633
## [1107,]  1.163628947 0.5003716
## [1108,]  1.097005069 0.4931183
## [1109,]  0.144963779 0.3894929
## [1110,] -1.044833457 0.3500223
## [1111,] -0.172624267 0.3632673
## [1112,] -0.018710856 0.3749426
## [1113,] -0.387672777 0.3509628
## [1114,]  0.406751189 0.4161066
## [1115,]  1.067301163 0.4898558
## [1116,]  0.917676235 0.4732017
## [1117,]  0.242326369 0.3989911
## [1118,]  1.845426522 0.5682556
## [1119,] -0.452313865 0.3483017
## [1120,] -0.938688015 0.3460510
## [1121,]  2.113748965 0.5920662
## [1122,] -0.303368910 0.3551781
## [1123,]  1.388993401 0.5241398
## [1124,]  0.159383646 0.3908641
## [1125,] -0.148640512 0.3649418
## [1126,] -0.104346880 0.3681795
## [1127,]  1.143489269 0.4981889
## [1128,]  1.223445608 0.5068012
## [1129,] -0.766129950 0.3430822
## [1130,]  0.163029877 0.3912128
## [1131,] -0.644961030 0.3435229
## [1132,] -0.473279361 0.3475491
## [1133,] -1.864016600 0.4330002
## [1134,] -0.210004752 0.3607717
## [1135,] -1.008022153 0.3484589
## [1136,]  0.406751189 0.4161066
## [1137,]  2.571997950 0.6312275
## [1138,] -0.284242313 0.3562470
## [1139,] -0.471782767 0.3476010
## [1140,] -0.907619800 0.3451992
## [1141,] -0.572675218 0.3447447
## [1142,] -0.030132453 0.3740041
## [1143,]  0.167119264 0.3916050
## [1144,]  0.174551761 0.3923203
## [1145,]  0.490995349 0.4252629
## [1146,]  0.419614473 0.4174907
## [1147,]  1.350994175 0.5202221
## [1148,]  0.990475554 0.4813457
## [1149,]  0.079595756 0.3834485
## [1150,] -0.115166538 0.3673716
## [1151,] -1.026230902 0.3492075
## [1152,]  0.130828328 0.3881616
## [1153,] -0.775929504 0.3431365
## [1154,] -0.921972476 0.3455753
## [1155,]  0.124474032 0.3875674
## [1156,]  0.914884461 0.4728882
## [1157,]  0.299564207 0.4048141
## [1158,]  0.382887707 0.4135539
## [1159,]  1.704537825 0.5551942
## [1160,] -0.412541142 0.3498789
## [1161,]  0.856203256 0.4662806
## [1162,]  1.179128339 0.5020454
## [1163,]  0.334301877 0.4084227
## [1164,]  0.864911266 0.4672629
## [1165,] -0.526534102 0.3458876
## [1166,]  0.282293423 0.4030402
## [1167,] -0.900577188 0.3450256
## [1168,] -1.293702536 0.3657489
## [1169,] -0.249586347 0.3582861
## [1170,]  0.627708731 0.4404739
## [1171,]  0.313387939 0.4062437
## [1172,]  0.609652096 0.4384472
## [1173,]  1.195843145 0.5038444
## [1174,] -0.937317953 0.3460105
## [1175,]  0.012218423 0.3775378
## [1176,]  0.674111100 0.4456986
## [1177,] -0.993827623 0.3479088
## [1178,]  0.471945740 0.4231746
## [1179,]  0.609087039 0.4383838
## [1180,] -0.442084962 0.3486887
## [1181,] -0.264498229 0.3573928
## [1182,] -0.496615901 0.3467765
## [1183,] -0.819721261 0.3435461
## [1184,] -0.135230005 0.3659024
## [1185,]  1.424057824 0.5277210
## [1186,]  0.201297757 0.3949217
## [1187,]  0.643446596 0.4422436
## [1188,]  0.049747564 0.3807880
## [1189,]  0.207925316 0.3955728
## [1190,] -1.604870236 0.3975264
## [1191,]  0.415521474 0.4170496
## [1192,] -0.180198114 0.3627503
## [1193,]  0.541304896 0.4308196
## [1194,] -0.239660428 0.3588939
## [1195,] -0.939774036 0.3460834
## [1196,] -1.608270993 0.3979428
## [1197,] -0.084043063 0.3697245
## [1198,] -1.465161299 0.3816726
## [1199,] -1.443954954 0.3794868
## [1200,] -1.131639047 0.3544912
## [1201,] -1.041188799 0.3498586
## [1202,] -1.499853054 0.3853762
## [1203,] -1.140408945 0.3550037
## [1204,] -0.806971621 0.3433986
## [1205,] -0.276206120 0.3567082
## [1206,] -1.202750173 0.3589670
## [1207,]  1.061979312 0.4892695
## [1208,] -0.458610089 0.3480699
## [1209,] -0.284242313 0.3562470
## [1210,]  2.406223499 0.6171067
## [1211,] -0.622807499 0.3438225
## [1212,] -0.597287836 0.3442499
## [1213,] -0.413348293 0.3498449
## [1214,]  1.576249549 0.5428840
## [1215,] -1.182318005 0.3576063
## [1216,]  0.381468708 0.4134028
## [1217,] -0.478838984 0.3473588
## [1218,]  0.269424539 0.4017278
## [1219,]  0.769194336 0.4564459
## [1220,]  0.511527044 0.4275237
## [1221,] -0.746056106 0.3430134
## [1222,]  1.423185812 0.5276323
## [1223,] -0.084861188 0.3696615
## [1224,]  0.160211663 0.3909432
## [1225,] -0.083649181 0.3697549
## [1226,] -1.693294021 0.4087991
## [1227,] -0.852689542 0.3440356
## [1228,] -0.672927263 0.3432404
## [1229,]  1.738575872 0.5583916
## [1230,]  1.179128339 0.5020454
## [1231,] -1.499853054 0.3853762
## [1232,] -0.673266707 0.3432376
## [1233,] -0.297052714 0.3555266
## [1234,]  0.914884461 0.4728882
## [1235,] -2.193610396 0.4868621
## [1236,] -1.126730361 0.3542093
## [1237,] -1.233461814 0.3611252
## [1238,]  1.129397337 0.4966564
## [1239,]  0.495195684 0.4257246
## 
## $scores$noDIF_conservative
##                   F1     SE_F1
##    [1,] -0.119788822 0.3670298
##    [2,]  0.235142472 0.3982720
##    [3,]  0.573613062 0.4344155
##    [4,]  0.735956027 0.4526857
##    [5,]  1.237616162 0.5083121
##    [6,] -0.026565524 0.3742960
##    [7,]  0.424283987 0.4179944
##    [8,] -0.732676204 0.3429991
##    [9,] -0.204114369 0.3611555
##   [10,]  0.859851975 0.4666922
##   [11,] -0.972208784 0.3471276
##   [12,] -1.045921602 0.3500715
##   [13,] -0.206881519 0.3609748
##   [14,] -0.154051933 0.3645591
##   [15,] -0.373441849 0.3516163
##   [16,]  0.990475554 0.4813457
##   [17,]  0.406751189 0.4161066
##   [18,]  0.560705465 0.4329766
##   [19,] -0.750774625 0.3430245
##   [20,] -0.958803823 0.3466775
##   [21,]  1.746234902 0.5591073
##   [22,]  0.174488560 0.3923142
##   [23,] -0.217474468 0.3602901
##   [24,]  1.012247365 0.4837672
##   [25,] -0.763386473 0.3430695
##   [26,] -0.976577554 0.3472800
##   [27,] -0.744947997 0.3430113
##   [28,]  0.090964580 0.3844787
##   [29,] -0.342899683 0.3530992
##   [30,] -0.365291532 0.3520014
##   [31,]  0.693216937 0.4478550
##   [32,] -0.627607560 0.3437520
##   [33,] -1.085779886 0.3519935
##   [34,]  0.324649773 0.4074147
##   [35,]  0.693216937 0.4478550
##   [36,]  0.448801323 0.4206508
##   [37,]  0.079939591 0.3834795
##   [38,] -0.572582465 0.3447467
##   [39,]  0.299564207 0.4048141
##   [40,] -0.786146575 0.3432076
##   [41,] -0.404686026 0.3502132
##   [42,]  0.874153953 0.4683049
##   [43,] -1.427695317 0.3778515
##   [44,] -0.704283332 0.3430518
##   [45,]  1.078705956 0.4911104
##   [46,] -1.408691205 0.3759852
##   [47,]  0.336511031 0.4086540
##   [48,]  1.179128339 0.5020454
##   [49,]  0.406751189 0.4161066
##   [50,]  0.111934763 0.3864027
##   [51,]  2.571997950 0.6312275
##   [52,] -0.167168605 0.3636432
##   [53,] -0.118670475 0.3671123
##   [54,]  0.856203256 0.4662806
##   [55,]  1.179128339 0.5020454
##   [56,] -1.226391295 0.3606164
##   [57,] -0.144607431 0.3652289
##   [58,] -0.199051218 0.3614883
##   [59,]  1.288904294 0.5137399
##   [60,] -0.226441676 0.3597196
##   [61,]  0.095368777 0.3848803
##   [62,]  0.537696269 0.4304192
##   [63,] -0.385185903 0.3510753
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##  [880,]  0.990475554 0.4813457
##  [881,] -0.644941142 0.3435232
##  [882,]  0.133933777 0.3884530
##  [883,]  1.541696742 0.5394957
##  [884,] -0.651444331 0.3434479
##  [885,] -0.417967786 0.3496523
##  [886,] -0.189844037 0.3621001
##  [887,] -0.520951341 0.3460447
##  [888,]  0.028962192 0.3789745
##  [889,]  1.494396464 0.5348058
##  [890,]  0.310093384 0.4059022
##  [891,] -0.491185901 0.3469501
##  [892,] -0.831741404 0.3437065
##  [893,] -0.167920060 0.3635913
##  [894,]  1.706868337 0.5554140
##  [895,] -0.376554346 0.3514713
##  [896,]  0.481877064 0.4242621
##  [897,]  0.134759990 0.3885306
##  [898,]  0.073735400 0.3829210
##  [899,] -1.380441943 0.3733015
##  [900,] -0.567591293 0.3448569
##  [901,] -0.754004346 0.3430338
##  [902,]  0.663954803 0.4445533
##  [903,]  0.637538655 0.4415789
##  [904,]  0.621077321 0.4397291
##  [905,] -0.899219423 0.3449930
##  [906,] -0.473279361 0.3475491
##  [907,] -0.644941142 0.3435232
##  [908,]  0.757766480 0.4551530
##  [909,] -0.082009010 0.3698814
##  [910,]  0.003103605 0.3767650
##  [911,] -0.982767735 0.3475007
##  [912,] -1.110906534 0.3533242
##  [913,]  0.471945740 0.4231746
##  [914,]  0.415521474 0.4170496
##  [915,] -0.501692906 0.3466175
##  [916,]  0.643424343 0.4422411
##  [917,] -0.577693640 0.3446373
##  [918,]  0.134759990 0.3885306
##  [919,]  1.214150745 0.5058075
##  [920,] -0.060628953 0.3715521
##  [921,]  0.253369612 0.4001019
##  [922,] -0.611846788 0.3439954
##  [923,]  0.693216937 0.4478550
##  [924,] -0.429474147 0.3491837
##  [925,] -0.463765525 0.3478838
##  [926,] -1.352375631 0.3707434
##  [927,]  0.116814391 0.3868547
##  [928,] -0.760627800 0.3430577
##  [929,]  0.079939591 0.3834795
##  [930,] -0.649438912 0.3434705
##  [931,] -1.684764636 0.4076720
##  [932,]  0.194033652 0.3942111
##  [933,] -0.309249791 0.3548576
##  [934,]  0.055880820 0.3813293
##  [935,] -1.609628939 0.3981094
##  [936,] -0.027492208 0.3742201
##  [937,]  0.028540011 0.3789380
##  [938,]  0.549160464 0.4316922
##  [939,] -0.482524487 0.3472347
##  [940,] -1.529441237 0.3886584
##  [941,] -0.234024491 0.3592437
##  [942,]  1.508618965 0.5362223
##  [943,]  0.609652096 0.4384472
##  [944,] -0.420294109 0.3495562
##  [945,] -1.588287070 0.3955162
##  [946,] -0.046933319 0.3726434
##  [947,] -0.141152402 0.3654761
##  [948,]  0.950845822 0.4769206
##  [949,]  1.706868337 0.5554140
##  [950,] -0.289964876 0.3559230
##  [951,] -1.152500185 0.3557285
##  [952,]  0.891462779 0.4702544
##  [953,] -0.284243870 0.3562470
##  [954,]  0.630130786 0.4407461
##  [955,] -0.931355330 0.3458374
##  [956,] -0.664778207 0.3433117
##  [957,]  0.311258478 0.4060229
##  [958,]  0.738803644 0.4530078
##  [959,]  0.073735400 0.3829210
##  [960,] -1.114948918 0.3535468
##  [961,] -0.104346880 0.3681795
##  [962,] -0.021604375 0.3747038
##  [963,]  0.457075306 0.4215513
##  [964,]  0.460415354 0.4219154
##  [965,] -0.757678833 0.3430463
##  [966,]  0.347183811 0.4097741
##  [967,]  0.003103605 0.3767650
##  [968,]  0.216542495 0.3964229
##  [969,] -0.726926806 0.3430007
##  [970,] -0.654987982 0.3434093
##  [971,]  0.609652096 0.4384472
##  [972,] -0.150651549 0.3647992
##  [973,]  0.097217693 0.3850493
##  [974,]  0.794213264 0.4592762
##  [975,] -1.887743016 0.4365936
##  [976,] -0.803917482 0.3433667
##  [977,] -0.118670475 0.3671123
##  [978,] -1.444397438 0.3795318
##  [979,]  1.183358362 0.5025013
##  [980,] -0.755672181 0.3430393
##  [981,] -0.289599860 0.3559435
##  [982,]  0.769194336 0.4564459
##  [983,]  0.609652096 0.4384472
##  [984,]  0.088289036 0.3842355
##  [985,] -0.302879577 0.3552049
##  [986,] -0.618213278 0.3438930
##  [987,] -0.322655507 0.3541417
##  [988,]  0.159178368 0.3908444
##  [989,]  1.092669542 0.4926432
##  [990,] -1.245454175 0.3620045
##  [991,]  0.549697475 0.4317519
##  [992,] -1.274125553 0.3641898
##  [993,] -0.054790629 0.3720154
##  [994,]  0.507978514 0.4271322
##  [995,]  0.537696269 0.4304192
##  [996,]  2.113748965 0.5920662
##  [997,] -0.732036337 0.3429990
##  [998,] -0.209526284 0.3608027
##  [999,] -0.030535438 0.3739712
## [1000,] -0.451094564 0.3483471
## [1001,]  0.311258478 0.4060229
## [1002,] -0.341888725 0.3531502
## [1003,]  0.086081207 0.3840351
## [1004,]  1.508618965 0.5362223
## [1005,]  2.113748965 0.5920662
## [1006,]  0.046927634 0.3805400
## [1007,]  0.481877064 0.4242621
## [1008,]  0.481877064 0.4242621
## [1009,] -0.454003839 0.3482390
## [1010,]  1.037088927 0.4865209
## [1011,]  1.508618965 0.5362223
## [1012,]  0.670606609 0.4453033
## [1013,] -1.648814340 0.4030138
## [1014,] -0.673266707 0.3432376
## [1015,] -0.495687186 0.3468059
## [1016,] -0.619508395 0.3438728
## [1017,]  0.609652096 0.4384472
## [1018,]  0.073735400 0.3829210
## [1019,]  0.539732105 0.4306451
## [1020,]  0.231027250 0.3978613
## [1021,]  0.158943517 0.3908220
## [1022,] -0.648532697 0.3434809
## [1023,]  1.067086218 0.4898321
## [1024,] -0.852689542 0.3440356
## [1025,] -0.083649181 0.3697549
## [1026,] -1.608270993 0.3979428
## [1027,]  1.427164102 0.5280367
## [1028,] -0.348310400 0.3528286
## [1029,]  0.350309851 0.4101030
## [1030,] -1.329745380 0.3687601
## [1031,] -1.195464275 0.3584749
## [1032,]  0.090538712 0.3844400
## [1033,]  0.512958568 0.4276817
## [1034,] -0.368584931 0.3518448
## [1035,] -0.473279361 0.3475491
## [1036,]  0.167119264 0.3916050
## [1037,] -0.215205560 0.3604357
## [1038,]  0.041983108 0.3801067
## [1039,]  0.318883675 0.4068145
## [1040,]  0.597827181 0.4371222
## [1041,] -0.704283332 0.3430518
## [1042,] -0.875947174 0.3444750
## [1043,]  0.023723143 0.3785226
## [1044,] -0.110018572 0.3677546
## [1045,] -0.277040826 0.3566600
## [1046,]  0.199179605 0.3947142
## [1047,]  0.692491220 0.4477730
## [1048,] -0.417443117 0.3496740
## [1049,] -0.606170270 0.3440912
## [1050,] -1.144572402 0.3552508
## [1051,] -0.807805297 0.3434076
## [1052,]  0.799428063 0.4598660
## [1053,] -0.495858749 0.3468004
## [1054,] -0.473279361 0.3475491
## [1055,]  0.402396771 0.4156393
## [1056,] -0.083076494 0.3697990
## [1057,]  0.098642592 0.3851797
## [1058,] -0.255013389 0.3579582
## [1059,] -0.244829019 0.3585761
## [1060,] -0.394226286 0.3506699
## [1061,] -1.086602352 0.3520356
## [1062,]  0.083852984 0.3838332
## [1063,]  0.252414481 0.4000055
## [1064,] -0.498064544 0.3467308
## [1065,] -0.500193792 0.3466641
## [1066,] -0.162276926 0.3639828
## [1067,] -0.627607560 0.3437520
## [1068,] -0.862757714 0.3442162
## [1069,]  0.284321086 0.4032478
## [1070,] -0.275986349 0.3567209
## [1071,]  0.549697475 0.4317519
## [1072,] -1.646578704 0.4027290
## [1073,] -0.721477211 0.3430064
## [1074,] -0.606681778 0.3440824
## [1075,]  0.990475554 0.4813457
## [1076,] -0.141152402 0.3654761
## [1077,] -0.343078531 0.3530902
## [1078,]  0.158943517 0.3908220
## [1079,]  0.068090949 0.3824153
## [1080,] -0.133751287 0.3660094
## [1081,] -0.166972560 0.3636568
## [1082,]  2.113748965 0.5920662
## [1083,] -0.562062872 0.3449828
## [1084,]  0.018770540 0.3780974
## [1085,]  0.055880820 0.3813293
## [1086,] -0.771633007 0.3431110
## [1087,]  0.360714423 0.4112007
## [1088,] -0.445367595 0.3485631
## [1089,] -0.320831810 0.3542379
## [1090,]  0.880316573 0.4689993
## [1091,] -0.666295184 0.3432977
## [1092,]  0.196112226 0.3944141
## [1093,]  0.094743247 0.3848232
## [1094,] -0.708124794 0.3430381
## [1095,] -1.920171194 0.4415872
## [1096,] -0.903206537 0.3450896
## [1097,]  0.819047580 0.4620843
## [1098,] -1.112311643 0.3534013
## [1099,]  0.637538655 0.4415789
## [1100,]  0.609652096 0.4384472
## [1101,] -0.723023409 0.3430044
## [1102,] -0.273283485 0.3568777
## [1103,] -0.647468339 0.3434932
## [1104,]  0.321382069 0.4070744
## [1105,] -1.151719643 0.3556810
## [1106,] -0.450660719 0.3483633
## [1107,]  1.163628947 0.5003716
## [1108,]  1.097005069 0.4931183
## [1109,]  0.144963779 0.3894929
## [1110,] -1.044833457 0.3500223
## [1111,] -0.172624267 0.3632673
## [1112,] -0.018710856 0.3749426
## [1113,] -0.387672777 0.3509628
## [1114,]  0.406751189 0.4161066
## [1115,]  1.067301163 0.4898558
## [1116,]  0.917676235 0.4732017
## [1117,]  0.242326369 0.3989911
## [1118,]  1.845426522 0.5682556
## [1119,] -0.452313865 0.3483017
## [1120,] -0.938688015 0.3460510
## [1121,]  2.113748965 0.5920662
## [1122,] -0.303368910 0.3551781
## [1123,]  1.388993401 0.5241398
## [1124,]  0.159383646 0.3908641
## [1125,] -0.148640512 0.3649418
## [1126,] -0.104346880 0.3681795
## [1127,]  1.143489269 0.4981889
## [1128,]  1.223445608 0.5068012
## [1129,] -0.766129950 0.3430822
## [1130,]  0.163029877 0.3912128
## [1131,] -0.644961030 0.3435229
## [1132,] -0.473279361 0.3475491
## [1133,] -1.864016600 0.4330002
## [1134,] -0.210004752 0.3607717
## [1135,] -1.008022153 0.3484589
## [1136,]  0.406751189 0.4161066
## [1137,]  2.571997950 0.6312275
## [1138,] -0.284242313 0.3562470
## [1139,] -0.471782767 0.3476010
## [1140,] -0.907619800 0.3451992
## [1141,] -0.572675218 0.3447447
## [1142,] -0.030132453 0.3740041
## [1143,]  0.167119264 0.3916050
## [1144,]  0.174551761 0.3923203
## [1145,]  0.490995349 0.4252629
## [1146,]  0.419614473 0.4174907
## [1147,]  1.350994175 0.5202221
## [1148,]  0.990475554 0.4813457
## [1149,]  0.079595756 0.3834485
## [1150,] -0.115166538 0.3673716
## [1151,] -1.026230902 0.3492075
## [1152,]  0.130828328 0.3881616
## [1153,] -0.775929504 0.3431365
## [1154,] -0.921972476 0.3455753
## [1155,]  0.124474032 0.3875674
## [1156,]  0.914884461 0.4728882
## [1157,]  0.299564207 0.4048141
## [1158,]  0.382887707 0.4135539
## [1159,]  1.704537825 0.5551942
## [1160,] -0.412541142 0.3498789
## [1161,]  0.856203256 0.4662806
## [1162,]  1.179128339 0.5020454
## [1163,]  0.334301877 0.4084227
## [1164,]  0.864911266 0.4672629
## [1165,] -0.526534102 0.3458876
## [1166,]  0.282293423 0.4030402
## [1167,] -0.900577188 0.3450256
## [1168,] -1.293702536 0.3657489
## [1169,] -0.249586347 0.3582861
## [1170,]  0.627708731 0.4404739
## [1171,]  0.313387939 0.4062437
## [1172,]  0.609652096 0.4384472
## [1173,]  1.195843145 0.5038444
## [1174,] -0.937317953 0.3460105
## [1175,]  0.012218423 0.3775378
## [1176,]  0.674111100 0.4456986
## [1177,] -0.993827623 0.3479088
## [1178,]  0.471945740 0.4231746
## [1179,]  0.609087039 0.4383838
## [1180,] -0.442084962 0.3486887
## [1181,] -0.264498229 0.3573928
## [1182,] -0.496615901 0.3467765
## [1183,] -0.819721261 0.3435461
## [1184,] -0.135230005 0.3659024
## [1185,]  1.424057824 0.5277210
## [1186,]  0.201297757 0.3949217
## [1187,]  0.643446596 0.4422436
## [1188,]  0.049747564 0.3807880
## [1189,]  0.207925316 0.3955728
## [1190,] -1.604870236 0.3975264
## [1191,]  0.415521474 0.4170496
## [1192,] -0.180198114 0.3627503
## [1193,]  0.541304896 0.4308196
## [1194,] -0.239660428 0.3588939
## [1195,] -0.939774036 0.3460834
## [1196,] -1.608270993 0.3979428
## [1197,] -0.084043063 0.3697245
## [1198,] -1.465161299 0.3816726
## [1199,] -1.443954954 0.3794868
## [1200,] -1.131639047 0.3544912
## [1201,] -1.041188799 0.3498586
## [1202,] -1.499853054 0.3853762
## [1203,] -1.140408945 0.3550037
## [1204,] -0.806971621 0.3433986
## [1205,] -0.276206120 0.3567082
## [1206,] -1.202750173 0.3589670
## [1207,]  1.061979312 0.4892695
## [1208,] -0.458610089 0.3480699
## [1209,] -0.284242313 0.3562470
## [1210,]  2.406223499 0.6171067
## [1211,] -0.622807499 0.3438225
## [1212,] -0.597287836 0.3442499
## [1213,] -0.413348293 0.3498449
## [1214,]  1.576249549 0.5428840
## [1215,] -1.182318005 0.3576063
## [1216,]  0.381468708 0.4134028
## [1217,] -0.478838984 0.3473588
## [1218,]  0.269424539 0.4017278
## [1219,]  0.769194336 0.4564459
## [1220,]  0.511527044 0.4275237
## [1221,] -0.746056106 0.3430134
## [1222,]  1.423185812 0.5276323
## [1223,] -0.084861188 0.3696615
## [1224,]  0.160211663 0.3909432
## [1225,] -0.083649181 0.3697549
## [1226,] -1.693294021 0.4087991
## [1227,] -0.852689542 0.3440356
## [1228,] -0.672927263 0.3432404
## [1229,]  1.738575872 0.5583916
## [1230,]  1.179128339 0.5020454
## [1231,] -1.499853054 0.3853762
## [1232,] -0.673266707 0.3432376
## [1233,] -0.297052714 0.3555266
## [1234,]  0.914884461 0.4728882
## [1235,] -2.193610396 0.4868621
## [1236,] -1.126730361 0.3542093
## [1237,] -1.233461814 0.3611252
## [1238,]  1.129397337 0.4966564
## [1239,]  0.495195684 0.4257246
## 
## $scores$anchor_liberal
##                F1     SE_F1
## 1     0.848284741 0.4630608
## 2     1.296178446 0.5024249
## 3     1.721665483 0.5476654
## 4     1.929425648 0.5709227
## 5     2.558998271 0.6403055
## 6     0.966936483 0.4723125
## 7     1.532044101 0.5269183
## 8     0.073521923 0.4324842
## 9     0.739905811 0.4555101
## 10    2.082588155 0.5881387
## 11   -0.225657281 0.4374464
## 12   -0.318132988 0.4410540
## 13    0.738871011 0.4554424
## 14    0.803352065 0.4598209
## 15    0.528737425 0.4435820
## 16    2.247404631 0.6065186
## 17    1.510860139 0.5246481
## 18    1.707369560 0.5460798
## 19    0.052709631 0.4325024
## 20   -0.208943076 0.4368996
## 21    3.200568665 0.7034359
## 22    1.217740062 0.4947455
## 23    0.723165215 0.4544260
## 24    2.275750024 0.6096520
## 25    0.037919909 0.4325445
## 26   -0.230313041 0.4376045
## 27    0.060056262 0.4324905
## 28    1.114172964 0.4850567
## 29    0.566538832 0.4454284
## 30    0.538753718 0.4440584
## 31    1.872120320 0.5644812
## 32    0.080626137 0.4177755
## 33   -0.369621000 0.4434902
## 34    1.406973502 0.5136995
## 35    1.872120320 0.5644812
## 36    1.564913658 0.5304627
## 37    1.099323184 0.4837138
## 38    0.276515026 0.4347849
## 39    1.376554863 0.5105588
## 40    0.008290807 0.4327025
## 41    0.489038978 0.4417856
## 42    2.101582680 0.5902680
## 43   -0.797663474 0.4754086
## 44    0.111160458 0.4325732
## 45    2.360222500 0.6189274
## 46   -0.775362834 0.4732442
## 47    1.422410778 0.5153053
## 48    2.485414707 0.6324727
## 49    1.510860139 0.5246481
## 50    1.140066191 0.4874272
## 51    4.211613833 0.7585069
## 52    0.787704729 0.4587285
## 53    0.849843144 0.4631759
## 54    2.077875971 0.5876102
## 55    2.485414707 0.6324727
## 56   -0.545465557 0.4541066
## 57    0.817555880 0.4608287
## 58    0.748515884 0.4560764
## 59    2.623957012 0.6471331
## 60    0.715109676 0.4539124
## 61    1.119738460 0.4855632
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## 1052  2.007701977 0.5797276
## 1053  0.373878046 0.4374314
## 1054  0.402482820 0.4383915
## 1055  1.507384475 0.5242768
## 1056  0.893506878 0.4664712
## 1057  1.121572498 0.4857304
## 1058  0.678415832 0.4516411
## 1059  0.692153728 0.4524783
## 1060  0.502027017 0.4423570
## 1061 -0.371066232 0.4435630
## 1062  1.104868429 0.4842138
## 1063  1.319239282 0.5047328
## 1064  0.368903099 0.4372728
## 1065  0.368913007 0.4372731
## 1066  0.796361495 0.4593305
## 1067  0.080626137 0.4177755
## 1068 -0.088255054 0.4339037
## 1069  1.359171343 0.5087788
## 1070  0.649148397 0.4499106
## 1071  1.693936072 0.5445923
## 1072 -1.073464814 0.5064173
## 1073  0.086245143 0.4324968
## 1074  0.236347810 0.4339791
## 1075  2.247404631 0.6065186
## 1076  0.821367322 0.4611017
## 1077  0.566338567 0.4454183
## 1078  1.198507775 0.4929056
## 1079  1.085947203 0.4825146
## 1080  0.831371980 0.4618236
## 1081  0.787711811 0.4587290
## 1082  3.659713220 0.7398797
## 1083  0.292187759 0.4351450
## 1084  1.024656266 0.4771524
## 1085  1.071057818 0.4811917
## 1086  0.026369635 0.4325944
## 1087  1.454167343 0.5186329
## 1088  0.437288558 0.4396689
## 1089  0.595738127 0.4469435
## 1090  2.109239263 0.5911256
## 1091  0.159460480 0.4329149
## 1092  1.247502117 0.4976270
## 1093  1.121609409 0.4857338
## 1094 -0.014274990 0.4181232
## 1095 -1.418379387 0.5550186
## 1096 -0.139414595 0.4349698
## 1097  2.031805157 0.5824371
## 1098 -0.403635593 0.4452672
## 1099  1.803097057 0.5567429
## 1100  1.766535614 0.5526587
## 1101  0.087575143 0.4324991
## 1102  0.654741274 0.4502356
## 1103  0.180687745 0.4331453
## 1104  1.405989489 0.5135974
## 1105 -0.450985755 0.4479624
## 1106  0.429979513 0.4393908
## 1107  2.467793004 0.6305821
## 1108  2.382431106 0.6213488
## 1109  1.182142243 0.4913541
## 1110 -0.317910414 0.4410441
## 1111  0.782363175 0.4583600
## 1112  0.974014814 0.4728946
## 1113  0.511107988 0.4427660
## 1114  1.510860139 0.5246481
## 1115  2.344924812 0.6172551
## 1116  2.156773470 0.5964408
## 1117  1.304195458 0.5032248
## 1118  3.324202071 0.7142476
## 1119  0.430678551 0.4394171
## 1120 -0.182956487 0.4361133
## 1121  3.659713220 0.7398797
## 1122  0.617433671 0.4481186
## 1123  2.750202019 0.6601510
## 1124  1.200770081 0.4931211
## 1125  0.812769147 0.4604873
## 1126  0.868764302 0.4645870
## 1127  2.440243853 0.6276156
## 1128  2.542855748 0.6385959
## 1129  0.032181212 0.4325674
## 1130  1.205803199 0.4936015
## 1131  0.185910365 0.4332095
## 1132  0.402482820 0.4383915
## 1133 -1.346376920 0.5440871
## 1134  0.733332767 0.4550817
## 1135 -0.270691836 0.4390800
## 1136  1.510860139 0.5246481
## 1137  4.211613833 0.7585069
## 1138  0.639649048 0.4493647
## 1139  0.403567924 0.4384295
## 1140 -0.145904177 0.4351265
## 1141  0.278085504 0.4348198
## 1142  0.962192256 0.4719241
## 1143  1.211044621 0.4941030
## 1144  1.218978411 0.4948646
## 1145  1.617934128 0.5362310
## 1146  1.529480974 0.5266430
## 1147  2.701900967 0.6552109
## 1148  2.247404631 0.6065186
## 1149  1.102440614 0.4839947
## 1150  0.854367415 0.4635109
## 1151 -0.294663700 0.4400450
## 1152  1.163700246 0.4896218
## 1153  0.020471385 0.4326257
## 1154 -0.161872054 0.4355324
## 1155  1.155346323 0.4888427
## 1156  2.152766291 0.5959934
## 1157  1.376554863 0.5105588
## 1158  1.481833583 0.5215570
## 1159  3.147576639 0.6986376
## 1160  0.477348394 0.4412850
## 1161  2.077875971 0.5876102
## 1162  2.485414707 0.6324727
## 1163  1.420166446 0.5150714
## 1164  2.089449964 0.5889082
## 1165  0.334566480 0.4362461
## 1166  1.356255032 0.5084813
## 1167 -0.137943466 0.4349350
## 1168 -0.711700710 0.4488050
## 1169  0.684091389 0.4519850
## 1170  1.790060505 0.5552852
## 1171  1.394561151 0.5124141
## 1172  1.766535614 0.5526587
## 1173  2.509426697 0.6350398
## 1174 -0.182407627 0.4360976
## 1175  1.014930968 0.4763223
## 1176  1.849411934 0.5619321
## 1177 -0.254358887 0.4384605
## 1178  1.595552389 0.5337888
## 1179  1.768210436 0.5528455
## 1180  0.442638121 0.4398757
## 1181  0.665803683 0.4508864
## 1182  0.373432754 0.4374171
## 1183 -0.035428501 0.4331158
## 1184  0.829183751 0.4616650
## 1185  2.795035669 0.6646896
## 1186  1.252795311 0.4981437
## 1187  1.811617331 0.5576964
## 1188  1.062988179 0.4804801
## 1189  1.261109849 0.4989579
## 1190 -1.080661766 0.4837982
## 1191  1.522494902 0.5258935
## 1192  0.771431704 0.4576126
## 1193  1.680858932 0.5431469
## 1194  0.697985586 0.4528385
## 1195 -0.184095243 0.4361461
## 1196 -1.025666287 0.5005017
## 1197  0.892139310 0.4663659
## 1198 -0.846825407 0.4803667
## 1199 -0.818642626 0.4774931
## 1200 -0.425771072 0.4464951
## 1201 -0.313316000 0.4408417
## 1202 -0.890245539 0.4849565
## 1203 -0.438434423 0.4472229
## 1204 -0.017568004 0.4329209
## 1205  0.652090787 0.4500812
## 1206 -0.515542645 0.4520506
## 1207  2.338083804 0.6165062
## 1208  0.420908950 0.4390529
## 1209  0.639649048 0.4493647
## 1210  4.017034182 0.7568267
## 1211  0.213686356 0.4335997
## 1212  0.247371675 0.4341834
## 1213  0.479273259 0.4413665
## 1214  2.985932332 0.6834789
## 1215 -0.490648107 0.4504177
## 1216  1.479857864 0.5213474
## 1217  0.394464935 0.4381142
## 1218  1.339239198 0.5067516
## 1219  1.968073317 0.5752703
## 1220  1.645264826 0.5392263
## 1221 -0.057469981 0.4185831
## 1222  2.794096335 0.6645950
## 1223  0.892517458 0.4663950
## 1224  1.200273699 0.4930738
## 1225  0.894164346 0.4665218
## 1226 -1.134407610 0.5142694
## 1227 -0.075579159 0.4336858
## 1228  0.150924209 0.4328360
## 1229  3.194749298 0.7029134
## 1230  2.485414707 0.6324727
## 1231 -0.890245539 0.4849565
## 1232  0.149180534 0.4328209
## 1233  0.459952293 0.4250934
## 1234  2.152766291 0.5959934
## 1235 -1.758844623 0.6110436
## 1236 -0.511711257 0.4350000
## 1237 -0.555166008 0.4547949
## 1238  2.426103539 0.6260879
## 1239  1.623637347 0.5368549
## 
## $scores$anchor_conservative
##                F1     SE_F1
## 1     0.848284741 0.4630608
## 2     1.296178446 0.5024249
## 3     1.721665483 0.5476654
## 4     1.929425648 0.5709227
## 5     2.558998271 0.6403055
## 6     0.966936483 0.4723125
## 7     1.532044101 0.5269183
## 8     0.073521923 0.4324842
## 9     0.739905811 0.4555101
## 10    2.082588155 0.5881387
## 11   -0.225657281 0.4374464
## 12   -0.318132988 0.4410540
## 13    0.738871011 0.4554424
## 14    0.803352065 0.4598209
## 15    0.528737425 0.4435820
## 16    2.247404631 0.6065186
## 17    1.510860139 0.5246481
## 18    1.707369560 0.5460798
## 19    0.052709631 0.4325024
## 20   -0.208943076 0.4368996
## 21    3.200568665 0.7034359
## 22    1.217740062 0.4947455
## 23    0.723165215 0.4544260
## 24    2.275750024 0.6096520
## 25    0.037919909 0.4325445
## 26   -0.230313041 0.4376045
## 27    0.060056262 0.4324905
## 28    1.114172964 0.4850567
## 29    0.566538832 0.4454284
## 30    0.538753718 0.4440584
## 31    1.872120320 0.5644812
## 32    0.080626137 0.4177755
## 33   -0.369621000 0.4434902
## 34    1.406973502 0.5136995
## 35    1.872120320 0.5644812
## 36    1.564913658 0.5304627
## 37    1.099323184 0.4837138
## 38    0.276515026 0.4347849
## 39    1.376554863 0.5105588
## 40    0.008290807 0.4327025
## 41    0.489038978 0.4417856
## 42    2.101582680 0.5902680
## 43   -0.797663474 0.4754086
## 44    0.111160458 0.4325732
## 45    2.360222500 0.6189274
## 46   -0.775362834 0.4732442
## 47    1.422410778 0.5153053
## 48    2.485414707 0.6324727
## 49    1.510860139 0.5246481
## 50    1.140066191 0.4874272
## 51    4.211613833 0.7585069
## 52    0.787704729 0.4587285
## 53    0.849843144 0.4631759
## 54    2.077875971 0.5876102
## 55    2.485414707 0.6324727
## 56   -0.545465557 0.4541066
## 57    0.817555880 0.4608287
## 58    0.748515884 0.4560764
## 59    2.623957012 0.6471331
## 60    0.715109676 0.4539124
## 61    1.119738460 0.4855632
## 62    1.678122478 0.5428447
## 63    0.513855603 0.4428913
## 64    2.407947843 0.6241215
## 65    1.625837357 0.5370957
## 66    0.457254932 0.4404550
## 67    1.040637214 0.4785291
## 68    2.152766291 0.5959934
## 69   -0.595557056 0.4577752
## 70    1.680858932 0.5431469
## 71   -0.419907373 0.4461643
## 72    2.905543592 0.6756760
## 73    1.457480669 0.5189819
## 74    1.121031181 0.4856811
## 75   -0.081116529 0.4337787
## 76    2.027183861 0.5819178
## 77    2.652712902 0.6501281
## 78    1.757565692 0.5516587
## 79    1.251535492 0.4980206
## 80    0.601729246 0.4472639
## 81    1.390806573 0.5120263
## 82    0.401902214 0.4383712
## 83   -0.457190832 0.4483346
## 84   -0.011330576 0.4328614
## 85    0.787711811 0.4587290
## 86    1.910270588 0.5687685
## 87    1.126686314 0.4861978
## 88    2.394998055 0.6227157
## 89    1.786167357 0.5548502
## 90    1.735737512 0.5492289
## 91    1.184390317 0.4915665
## 92    0.739875510 0.4555081
## 93    4.211613833 0.7585069
## 94   -0.293446558 0.4399944
## 95   -0.575716368 0.4562883
## 96    1.142173432 0.4876217
## 97    1.650419356 0.5397928
## 98   -0.435937724 0.4470779
## 99    0.139203792 0.4327406
## 100   1.444797005 0.5176478
## 101   0.995205434 0.4746566
## 102  -0.698663598 0.4662106
## 103  -0.390728405 0.4445772
## 104   0.589977576 0.4466386
## 105  -0.137557286 0.4349259
## 106   0.751490389 0.4562735
## 107   1.977140693 0.5762903
## 108  -1.310718906 0.5388158
## 109   1.896665741 0.5672390
## 110   0.969520191 0.4725246
## 111   2.902062939 0.6753345
## 112   0.309115047 0.4355627
## 113   2.404150794 0.6237096
## 114   0.735890027 0.4552479
## 115   1.092161377 0.4830704
## 116   1.121875906 0.4857581
## 117   4.211613833 0.7585069
## 118   0.049331789 0.4325098
## 119   0.508971324 0.4426691
## 120  -0.448109076 0.4477913
## 121   0.829257915 0.4616704
## 122   0.784019511 0.4584740
## 123  -0.359586689 0.4429914
## 124  -1.898253251 0.6355087
## 125  -0.550642603 0.4544726
## 126   0.001814362 0.4327502
## 127   0.721395360 0.4543127
## 128  -0.108513532 0.4342901
## 129   2.306263696 0.6130138
## 130   3.496331268 0.7282089
## 131   0.554196069 0.4448111
## 132   0.691123506 0.4524150
## 133   2.485414707 0.6324727
## 134   1.787324909 0.5549795
## 135   0.984708121 0.4737801
## 136   0.537814625 0.4440133
## 137   2.077875971 0.5876102
## 138   0.807930829 0.4601441
## 139   0.192272705 0.4332916
## 140   2.125675192 0.5929653
## 141  -0.238601098 0.4378920
## 142   3.091487851 0.6934631
## 143   3.849021117 0.7506670
## 144   0.087575143 0.4324991
## 145   0.003393134 0.4327381
## 146  -0.387837579 0.4444253
## 147   0.707976173 0.4534621
## 148   1.839422760 0.5608117
## 149   1.444797005 0.5176478
## 150   0.148733025 0.4328171
## 151   1.605838615 0.5349099
## 152   1.139735927 0.4873967
## 153   0.706406994 0.4533636
## 154   1.787920607 0.5550461
## 155   1.957712314 0.5741047
## 156  -0.488000287 0.4502482
## 157   1.766535614 0.5526587
## 158   1.680858932 0.5431469
## 159   0.708027458 0.4534653
## 160   1.273647632 0.5001914
## 161   1.849411934 0.5619321
## 162  -0.430087636 0.4467411
## 163   1.437162901 0.5168472
## 164   0.377721295 0.4375557
## 165   0.679475288 0.4517051
## 166   2.420325847 0.6254627
## 167   2.550430967 0.6393988
## 168   1.196734589 0.4927369
## 169   0.658635992 0.4504635
## 170   1.546934643 0.5285207
## 171   2.275750024 0.6096520
## 172  -0.512019462 0.4518152
## 173   2.197401226 0.6009686
## 174  -0.377149213 0.4438720
## 175   1.522494902 0.5258935
## 176  -1.375473632 0.5484594
## 177   2.794096335 0.6645950
## 178   2.058669778 0.5854548
## 179   2.437240777 0.6272914
## 180   0.114389465 0.4325881
## 181  -0.430842291 0.4305363
## 182   3.843526490 0.7504054
## 183  -0.024265793 0.4329898
## 184   1.106497348 0.4843610
## 185   1.243345573 0.4972221
## 186   0.309115047 0.4355627
## 187   1.603387415 0.5346426
## 188   2.509470781 0.6350445
## 189   1.968073317 0.5752703
## 190   2.046171824 0.5840513
## 191  -1.223170209 0.5263001
## 192  -1.025666287 0.5005017
## 193   3.043106901 0.6889253
## 194   0.002742828 0.4327430
## 195   0.965710575 0.4722120
## 196   0.623555491 0.4484577
## 197   1.389288768 0.5118697
## 198   1.454121849 0.5186282
## 199   0.665803683 0.4508864
## 200   0.790845879 0.4589463
## 201   0.887367594 0.4659996
## 202   1.278798958 0.5007001
## 203   1.931218359 0.5711243
## 204   1.116736718 0.4852898
## 205  -0.741946459 0.4701012
## 206   2.333495667 0.6160035
## 207   2.464761472 0.6302563
## 208   0.105290575 0.4325490
## 209   1.385789007 0.5115088
## 210   0.871380639 0.4647842
## 211   1.949010327 0.5731257
## 212   0.790845879 0.4589463
## 213   0.609779578 0.4476993
## 214   3.719216253 0.7436341
## 215   2.197401226 0.6009686
## 216   0.836304108 0.4621822
## 217   1.255786106 0.4984362
## 218   0.098517682 0.4325259
## 219   1.559044031 0.5298279
## 220   2.291467739 0.6113852
## 221  -0.006027401 0.4328142
## 222   1.700307245 0.5452975
## 223   0.639649048 0.4493647
## 224   0.416843434 0.4389041
## 225   0.059227344 0.4324915
## 226   0.313419204 0.4356736
## 227   1.900775897 0.5677011
## 228   0.061971616 0.4324883
## 229  -0.114644409 0.4344163
## 230   1.023732787 0.4770733
## 231   0.402773150 0.4384017
## 232   1.564132305 0.5303781
## 233   0.413735117 0.4387914
## 234   3.200568665 0.7034359
## 235   1.405155060 0.5135108
## 236  -1.636796480 0.5902485
## 237   1.497944874 0.5232699
## 238   2.485414707 0.6324727
## 239   1.200273699 0.4930738
## 240  -0.832210532 0.4788661
## 241   2.164242177 0.5972743
## 242   2.542855748 0.6385959
## 243   0.044620132 0.4325224
## 244  -0.733961405 0.4693681
## 245   1.878440887 0.5651911
## 246   0.103934235 0.4325440
## 247   1.359651071 0.5088278
## 248   0.402482820 0.4383915
## 249   1.827858812 0.5595154
## 250   0.741774763 0.4556325
## 251  -0.285746555 0.4396783
## 252   1.832723344 0.5600606
## 253   2.306263696 0.6130138
## 254   1.142278446 0.4876314
## 255   1.359002635 0.5087616
## 256  -0.958355034 0.4925460
## 257   1.825322311 0.5592312
## 258   0.922941295 0.4687687
## 259   1.208773305 0.4938855
## 260   0.135278996 0.4327120
## 261   3.379731548 0.7189057
## 262   2.167787158 0.5976697
## 263  -0.564644845 0.4554778
## 264   1.315477937 0.5043549
## 265   1.071106759 0.4811961
## 266  -0.399801354 0.4289982
## 267   0.453230105 0.4402934
## 268  -0.295629357 0.4400852
## 269   1.061494061 0.4803488
## 270   2.309931624 0.6134171
## 271   0.031196366 0.4325718
## 272  -1.286872574 0.5079441
## 273  -1.170530846 0.5190824
## 274   1.163700246 0.4896218
## 275   0.256155131 0.4343553
## 276   0.122556169 0.4326308
## 277   1.376554863 0.5105588
## 278   1.200273699 0.4930738
## 279  -0.875431991 0.4833686
## 280  -0.927528885 0.4890527
## 281   0.083788595 0.4324930
## 282   0.733332767 0.4550817
## 283   2.623957012 0.6471331
## 284   0.906968611 0.4675145
## 285   1.297690578 0.5025756
## 286  -0.704271797 0.4667031
## 287   1.680858932 0.5431469
## 288  -0.983087596 0.4954174
## 289  -0.040019230 0.4331717
## 290  -0.676952613 0.4643363
## 291   0.373432754 0.4374171
## 292   0.714502698 0.4538740
## 293   1.150475772 0.4883902
## 294   2.902062939 0.6753345
## 295   0.635127056 0.4491075
## 296   1.444797005 0.5176478
## 297   2.027175290 0.5819168
## 298   0.201916529 0.4334243
## 299  -0.024281306 0.4329900
## 300   2.485414707 0.6324727
## 301   1.488880820 0.5223053
## 302   2.494785737 0.6334758
## 303   0.245124600 0.4341407
## 304  -0.332253933 0.4416917
## 305   2.012935040 0.5803160
## 306   1.460466623 0.5192967
## 307   2.112649894 0.5915075
## 308   1.043112968 0.4787437
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## 823   2.275750024 0.6096520
## 824   2.082588155 0.5881387
## 825   0.821367322 0.4611017
## 826   0.457794675 0.4404768
## 827   0.830345620 0.4617492
## 828   1.658516585 0.5406835
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## 830   2.102167962 0.5903335
## 831   1.043681655 0.4787931
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## 834   0.958903416 0.4716558
## 835   1.766535614 0.5526587
## 836   1.636412574 0.5382547
## 837   1.091543798 0.4830151
## 838   0.643641594 0.4495932
## 839   0.618240419 0.4481631
## 840   0.686814473 0.4521510
## 841   1.872120320 0.5644812
## 842   0.842887397 0.4626637
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## 844   0.440852150 0.4398063
## 845   0.719987917 0.4542228
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## 883   2.945569639 0.6795818
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## 885   0.473834819 0.4411371
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## 887   0.341767297 0.4364515
## 888   1.035691993 0.4781014
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## 890   1.389159027 0.5118563
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## 893   0.787654925 0.4587251
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## 904   1.784798050 0.5546972
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## 907   0.185596274 0.4332055
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## 911  -0.237323159 0.4378471
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## 921   1.319560447 0.5047651
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## 970   0.173376237 0.4330605
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## 984   1.110281987 0.4847037
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## 987   0.592269117 0.4467595
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## 1138  0.639649048 0.4493647
## 1139  0.403567924 0.4384295
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## 1141  0.278085504 0.4348198
## 1142  0.962192256 0.4719241
## 1143  1.211044621 0.4941030
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## 1156  2.152766291 0.5959934
## 1157  1.376554863 0.5105588
## 1158  1.481833583 0.5215570
## 1159  3.147576639 0.6986376
## 1160  0.477348394 0.4412850
## 1161  2.077875971 0.5876102
## 1162  2.485414707 0.6324727
## 1163  1.420166446 0.5150714
## 1164  2.089449964 0.5889082
## 1165  0.334566480 0.4362461
## 1166  1.356255032 0.5084813
## 1167 -0.137943466 0.4349350
## 1168 -0.711700710 0.4488050
## 1169  0.684091389 0.4519850
## 1170  1.790060505 0.5552852
## 1171  1.394561151 0.5124141
## 1172  1.766535614 0.5526587
## 1173  2.509426697 0.6350398
## 1174 -0.182407627 0.4360976
## 1175  1.014930968 0.4763223
## 1176  1.849411934 0.5619321
## 1177 -0.254358887 0.4384605
## 1178  1.595552389 0.5337888
## 1179  1.768210436 0.5528455
## 1180  0.442638121 0.4398757
## 1181  0.665803683 0.4508864
## 1182  0.373432754 0.4374171
## 1183 -0.035428501 0.4331158
## 1184  0.829183751 0.4616650
## 1185  2.795035669 0.6646896
## 1186  1.252795311 0.4981437
## 1187  1.811617331 0.5576964
## 1188  1.062988179 0.4804801
## 1189  1.261109849 0.4989579
## 1190 -1.080661766 0.4837982
## 1191  1.522494902 0.5258935
## 1192  0.771431704 0.4576126
## 1193  1.680858932 0.5431469
## 1194  0.697985586 0.4528385
## 1195 -0.184095243 0.4361461
## 1196 -1.025666287 0.5005017
## 1197  0.892139310 0.4663659
## 1198 -0.846825407 0.4803667
## 1199 -0.818642626 0.4774931
## 1200 -0.425771072 0.4464951
## 1201 -0.313316000 0.4408417
## 1202 -0.890245539 0.4849565
## 1203 -0.438434423 0.4472229
## 1204 -0.017568004 0.4329209
## 1205  0.652090787 0.4500812
## 1206 -0.515542645 0.4520506
## 1207  2.338083804 0.6165062
## 1208  0.420908950 0.4390529
## 1209  0.639649048 0.4493647
## 1210  4.017034182 0.7568267
## 1211  0.213686356 0.4335997
## 1212  0.247371675 0.4341834
## 1213  0.479273259 0.4413665
## 1214  2.985932332 0.6834789
## 1215 -0.490648107 0.4504177
## 1216  1.479857864 0.5213474
## 1217  0.394464935 0.4381142
## 1218  1.339239198 0.5067516
## 1219  1.968073317 0.5752703
## 1220  1.645264826 0.5392263
## 1221 -0.057469981 0.4185831
## 1222  2.794096335 0.6645950
## 1223  0.892517458 0.4663950
## 1224  1.200273699 0.4930738
## 1225  0.894164346 0.4665218
## 1226 -1.134407610 0.5142694
## 1227 -0.075579159 0.4336858
## 1228  0.150924209 0.4328360
## 1229  3.194749298 0.7029134
## 1230  2.485414707 0.6324727
## 1231 -0.890245539 0.4849565
## 1232  0.149180534 0.4328209
## 1233  0.459952293 0.4250934
## 1234  2.152766291 0.5959934
## 1235 -1.758844623 0.6110436
## 1236 -0.511711257 0.4350000
## 1237 -0.555166008 0.4547949
## 1238  2.426103539 0.6260879
## 1239  1.623637347 0.5368549
## 
## 
## $fits
## $fits$original
## 
## Call:
## mirt(data = items, model = model, method = method, verbose = messages, 
##     technical = technical)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 34 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: BFGS 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -11437.09
## Estimated parameters: 40 
## AIC = 22954.17
## BIC = 23159.06; SABIC = 23032
## G2 (1048535) = 6300.61, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$noDIF_liberal
## 
## Call:
## mirt(data = items, model = mirt.model(model_noDIF_liberal_Q), 
##     method = method, verbose = messages, technical = technical)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 34 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: BFGS 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -11437.09
## Estimated parameters: 40 
## AIC = 22954.17
## BIC = 23159.06; SABIC = 23032
## G2 (1048535) = 6300.61, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$noDIF_conservative
## 
## Call:
## mirt(data = items, model = mirt.model(model_noDIF_conservative_Q), 
##     method = method, verbose = messages, technical = technical)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 34 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: BFGS 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -11437.09
## Estimated parameters: 40 
## AIC = 22954.17
## BIC = 23159.06; SABIC = 23032
## G2 (1048535) = 6300.61, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$anchor_liberal
## 
## Call:
## multipleGroup(data = items, model = model, group = group, invariance = c(items_noDIF_liberal %>% 
##     names(), "free_means", "free_var"), method = method, technical = technical, 
##     verbose = messages)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 483 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: nlminb 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -11427.48
## Estimated parameters: 82 
## AIC = 22938.96
## BIC = 23154.09; SABIC = 23020.68
## G2 (2097108) = 6517.57, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## $fits$anchor_conservative
## 
## Call:
## multipleGroup(data = items, model = model, group = group, invariance = c(items_noDIF_conservative %>% 
##     names(), "free_means", "free_var"), method = method, technical = technical, 
##     verbose = messages)
## 
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 483 EM iterations.
## mirt version: 1.36.1 
## M-step optimizer: nlminb 
## EM acceleration: Ramsay 
## Number of rectangular quadrature: 61
## Latent density type: Gaussian 
## 
## Log-likelihood = -11427.48
## Estimated parameters: 82 
## AIC = 22938.96
## BIC = 23154.09; SABIC = 23020.68
## G2 (2097108) = 6517.57, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
## 
## 
## $DIF_stats
##       item converged    AIC SABIC    HQ    BIC    X2 df     p number  p_adj
## 1   PFA1_r      TRUE -1.944 1.948 1.909  8.300 5.944  2 0.051      1  1.024
## 2   PFA2_r      TRUE  2.042 5.933 5.895 12.286 1.958  2 0.376      2  7.515
## 3   PFA3_r      TRUE  2.784 6.676 6.637 13.029 1.216  2 0.545      3 10.891
## 4   PFA4_r      TRUE  1.893 5.784 5.746 12.137 2.107  2 0.349      4  6.975
## 5   PFA5_r      TRUE  1.963 5.854 5.815 12.207 2.037  2 0.361      5  7.222
## 6   PFA6_r      TRUE  3.740 7.631 7.593 13.984 0.260  2 0.878      6 17.562
## 7   PFA7_r      TRUE  0.233 4.124 4.086 10.477 3.767  2 0.152      7  3.041
## 8   PFA8_r      TRUE  1.817 5.708 5.669 12.061 2.183  2 0.336      8  6.713
## 9   PFA9_r      TRUE  2.607 6.498 6.460 12.851 1.393  2 0.498      9  9.968
## 10 PFA10_r      TRUE  1.882 5.773 5.735 12.126 2.118  2 0.347     10  6.936
## 11  PFB1_r      TRUE  3.782 7.673 7.635 14.026 0.218  2 0.897     11 17.937
## 12  PFB2_r      TRUE  3.216 7.107 7.069 13.460 0.784  2 0.676     12 13.513
## 13  PFB3_r      TRUE  2.268 6.159 6.120 12.512 1.732  2 0.421     13  8.411
## 14  PFB4_r      TRUE  1.846 5.737 5.699 12.090 2.154  2 0.341     14  6.812
## 15  PFB5_r      TRUE  1.656 5.548 5.509 11.901 2.344  2 0.310     15  6.196
## 16  PFB6_r      TRUE  3.989 7.880 7.842 14.233 0.011  2 0.994     16 19.890
## 17  PFB7_r      TRUE  3.563 7.454 7.416 13.807 0.437  2 0.804     17 16.073
## 18  PFB8_r      TRUE  1.319 5.210 5.172 11.563 2.681  2 0.262     18  5.234
## 19  PFB9_r      TRUE  3.391 7.282 7.244 13.635 0.609  2 0.738     19 14.752
## 20 PFB10_r      TRUE  1.649 5.540 5.502 11.893 2.351  2 0.309     20  6.173
## 
## $effect_size_items
## $effect_size_items$liberal
##         SIDS UIDS SIDN UIDN ESSD theta.of.max.D max.D mean.ES.foc mean.ES.ref
## item.1     0    0    0    0    0          0.848     0       0.921       0.921
## item.2     0    0    0    0    0          0.848     0       0.663       0.663
## item.3     0    0    0    0    0          0.848     0       0.528       0.528
## item.4     0    0    0    0    0          0.848     0       0.650       0.650
## item.5     0    0    0    0    0          0.848     0       0.589       0.589
## item.6     0    0    0    0    0          0.848     0       0.755       0.755
## item.7     0    0    0    0    0          0.848     0       0.257       0.257
## item.8     0    0    0    0    0          0.848     0       0.482       0.482
## item.9     0    0    0    0    0          0.848     0       0.071       0.071
## item.10    0    0    0    0    0          0.848     0       0.235       0.235
## item.11    0    0    0    0    0          0.848     0       0.970       0.970
## item.12    0    0    0    0    0          0.848     0       0.785       0.785
## item.13    0    0    0    0    0          0.848     0       0.887       0.887
## item.14    0    0    0    0    0          0.848     0       0.793       0.793
## item.15    0    0    0    0    0          0.848     0       0.319       0.319
## item.16    0    0    0    0    0          0.848     0       0.690       0.690
## item.17    0    0    0    0    0          0.848     0       0.495       0.495
## item.18    0    0    0    0    0          0.848     0       0.135       0.135
## item.19    0    0    0    0    0          0.848     0       0.510       0.510
## item.20    0    0    0    0    0          0.848     0       0.069       0.069
## 
## $effect_size_items$conservative
##         SIDS UIDS SIDN UIDN ESSD theta.of.max.D max.D mean.ES.foc mean.ES.ref
## item.1     0    0    0    0    0          0.848     0       0.921       0.921
## item.2     0    0    0    0    0          0.848     0       0.663       0.663
## item.3     0    0    0    0    0          0.848     0       0.528       0.528
## item.4     0    0    0    0    0          0.848     0       0.650       0.650
## item.5     0    0    0    0    0          0.848     0       0.589       0.589
## item.6     0    0    0    0    0          0.848     0       0.755       0.755
## item.7     0    0    0    0    0          0.848     0       0.257       0.257
## item.8     0    0    0    0    0          0.848     0       0.482       0.482
## item.9     0    0    0    0    0          0.848     0       0.071       0.071
## item.10    0    0    0    0    0          0.848     0       0.235       0.235
## item.11    0    0    0    0    0          0.848     0       0.970       0.970
## item.12    0    0    0    0    0          0.848     0       0.785       0.785
## item.13    0    0    0    0    0          0.848     0       0.887       0.887
## item.14    0    0    0    0    0          0.848     0       0.793       0.793
## item.15    0    0    0    0    0          0.848     0       0.319       0.319
## item.16    0    0    0    0    0          0.848     0       0.690       0.690
## item.17    0    0    0    0    0          0.848     0       0.495       0.495
## item.18    0    0    0    0    0          0.848     0       0.135       0.135
## item.19    0    0    0    0    0          0.848     0       0.510       0.510
## item.20    0    0    0    0    0          0.848     0       0.069       0.069
## 
## 
## $effect_size_test
## $effect_size_test$liberal
##           Effect Size     Value
## 1                STDS 0.0000000
## 2                UTDS 0.0000000
## 3              UETSDS 0.0000000
## 4               ETSSD 0.0000000
## 5         Starks.DTFR 0.0000000
## 6               UDTFR 0.0000000
## 7              UETSDN 0.0000000
## 8 theta.of.max.test.D 0.8482847
## 9           Test.Dmax 0.0000000
## 
## $effect_size_test$conservative
##           Effect Size     Value
## 1                STDS 0.0000000
## 2                UTDS 0.0000000
## 3              UETSDS 0.0000000
## 4               ETSSD 0.0000000
## 5         Starks.DTFR 0.0000000
## 6               UDTFR 0.0000000
## 7              UETSDN 0.0000000
## 8 theta.of.max.test.D 0.8482847
## 9           Test.Dmax 0.0000000

Bootstrapped confidence intervals

#1b
set.seed(1)
d1b_bootstrap_results = bootstrap_gaps(
  d1b_bw %>% select(SynA1_r:SynA25_r) %>% select(-SynA12_r),
  group = d1b_bw$Race
  )

quantile(d1b_bootstrap_results$d, probs = c(.025, .975))

##       2.5%      97.5% 
## -1.0986060 -0.3029647

quantile(d1b_bootstrap_results$d_adjusted, probs = c(.025, .975))

##       2.5%      97.5% 
## -1.4601850 -0.3784857

#1c
set.seed(1)
d1c_bootstrap_results = bootstrap_gaps(
  d1c_bw %>% select(PFA1_r:PFA10_r),
  group = d1c_bw$Race
  )

quantile(d1c_bootstrap_results$d, probs = c(.025, .975))

##       2.5%      97.5% 
## -0.9115643 -0.7280661

quantile(d1c_bootstrap_results$d_adjusted, probs = c(.025, .975))

##       2.5%      97.5% 
## -1.0683321 -0.8554621

#234
set.seed(1)
d234_bootstrap_results = bootstrap_gaps(
  d234_bw %>% select(PFA1_r:PFB10_r),
  group = d234_bw$Race
  )

quantile(d234_bootstrap_results$d, probs = c(.025, .975))

##       2.5%      97.5% 
## -1.0953240 -0.4806189

quantile(d234_bootstrap_results$d_adjusted, probs = c(.025, .975))

##      2.5%     97.5% 
## -1.236877 -0.531568

Meta-analysis

tibble(
  study = c("1b", "1c", "2-3"),
  d = c(
    mean(d1b$g[d1b$Race=="Black"]),
    mean(d1c$g[d1c$Race=="Black"]),
    mean(d234$g[d234$Race=="Black"])
  ),
  d_adjusted = c(
    c(
    mean(d1b$g[d1b$Race=="Black"]) %>% adj_d_reliability(empirical_rxx(s1b_mirt_fit_scores)),
    
    mean(d1c$g[d1c$Race=="Black"]) %>% adj_d_reliability(empirical_rxx(s1c_mirt_fit_scores)),
    
    mean(d234$g[d234$Race=="Black"]) %>% adj_d_reliability(empirical_rxx(s234_mirt_fit_scores))
  )
  ),
  d_se = c(
    d1b_bootstrap_results$d %>% sd(),
    d1c_bootstrap_results$d %>% sd(),
    d234_bootstrap_results$d %>% sd()
  ),
  d_adjusted_se = c(
    d1b_bootstrap_results$d_adjusted %>% sd(),
    d1c_bootstrap_results$d_adjusted %>% sd(),
    d234_bootstrap_results$d_adjusted %>% sd()
  )
) -> study_data

study_data

#meta analysis
rma(
  yi = study_data$d,
  sei = study_data$d_se
)

## 
## Random-Effects Model (k = 3; tau^2 estimator: REML)
## 
## tau^2 (estimated amount of total heterogeneity): 0 (SE = 0.0151)
## tau (square root of estimated tau^2 value):      0
## I^2 (total heterogeneity / total variability):   0.00%
## H^2 (total variability / sampling variability):  1.00
## 
## Test for Heterogeneity:
## Q(df = 2) = 0.5051, p-val = 0.7768
## 
## Model Results:
## 
## estimate      se      zval    pval    ci.lb    ci.ub     ​ 
##  -0.8351  0.0435  -19.1846  <.0001  -0.9204  -0.7498  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

rma(
  yi = study_data$d_adjusted,
  sei = study_data$d_adjusted_se
)

## 
## Random-Effects Model (k = 3; tau^2 estimator: REML)
## 
## tau^2 (estimated amount of total heterogeneity): 0 (SE = 0.0218)
## tau (square root of estimated tau^2 value):      0
## I^2 (total heterogeneity / total variability):   0.00%
## H^2 (total variability / sampling variability):  1.00
## 
## Test for Heterogeneity:
## Q(df = 2) = 0.5235, p-val = 0.7697
## 
## Model Results:
## 
## estimate      se      zval    pval    ci.lb    ci.ub     ​ 
##  -0.9877  0.0519  -19.0271  <.0001  -1.0895  -0.8860  *** 
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Meta

write_sessioninfo()

## R version 4.2.0 (2022-04-22)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Linux Mint 19.3
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=en_DK.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_DK.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_DK.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] metafor_3.4-0         metadat_1.2-0         Matrix_1.4-1         
##  [4] furrr_0.3.0           future_1.25.0         mirt_1.36.1          
##  [7] haven_2.5.0           kirkegaard_2022-08-25 psych_2.2.3          
## [10] assertthat_0.2.1      weights_1.0.4         Hmisc_4.7-0          
## [13] Formula_1.2-4         survival_3.2-13       lattice_0.20-45      
## [16] magrittr_2.0.3        forcats_0.5.1         stringr_1.4.0        
## [19] dplyr_1.0.9           purrr_0.3.4           readr_2.1.2          
## [22] tidyr_1.2.0           tibble_3.1.7          ggplot2_3.3.6        
## [25] tidyverse_1.3.1      
## 
## loaded via a namespace (and not attached):
##  [1] minqa_1.2.4          colorspace_2.0-3     ellipsis_0.3.2      
##  [4] htmlTable_2.4.0      base64enc_0.1-3      fs_1.5.2            
##  [7] rstudioapi_0.13      mice_3.14.0          farver_2.1.0        
## [10] listenv_0.8.0        Deriv_4.1.3          fansi_1.0.3         
## [13] lubridate_1.8.0      mathjaxr_1.6-0       xml2_1.3.3          
## [16] codetools_0.2-18     splines_4.2.0        mnormt_2.0.2        
## [19] knitr_1.39           jsonlite_1.8.0       nloptr_2.0.1        
## [22] broom_0.8.0          cluster_2.1.3        dbplyr_2.1.1        
## [25] png_0.1-7            compiler_4.2.0       httr_1.4.3          
## [28] backports_1.4.1      fastmap_1.1.0        cli_3.3.0           
## [31] htmltools_0.5.2      tools_4.2.0          gtable_0.3.0        
## [34] glue_1.6.2           Rcpp_1.0.8.3         cellranger_1.1.0    
## [37] jquerylib_0.1.4      vctrs_0.4.1          gdata_2.18.0        
## [40] nlme_3.1-157         xfun_0.30            globals_0.14.0      
## [43] lme4_1.1-29          rvest_1.0.2          lifecycle_1.0.1     
## [46] dcurver_0.9.2        gtools_3.9.2         MASS_7.3-57         
## [49] scales_1.2.0         hms_1.1.1            parallel_4.2.0      
## [52] RColorBrewer_1.1-3   yaml_2.3.5           pbapply_1.5-0       
## [55] gridExtra_2.3        sass_0.4.1           rpart_4.1.16        
## [58] latticeExtra_0.6-29  stringi_1.7.6        highr_0.9           
## [61] checkmate_2.1.0      permute_0.9-7        boot_1.3-28         
## [64] rlang_1.0.2          pkgconfig_2.0.3      evaluate_0.15       
## [67] labeling_0.4.2       htmlwidgets_1.5.4    tidyselect_1.1.2    
## [70] parallelly_1.31.1    plyr_1.8.7           R6_2.5.1            
## [73] generics_0.1.2       DBI_1.1.2            pillar_1.7.0        
## [76] foreign_0.8-82       withr_2.5.0          mgcv_1.8-40         
## [79] nnet_7.3-17          modelr_0.1.8         crayon_1.5.1        
## [82] utf8_1.2.2           tmvnsim_1.0-2        tzdb_0.3.0          
## [85] rmarkdown_2.14       jpeg_0.1-9           grid_4.2.0          
## [88] readxl_1.4.0         data.table_1.14.2    vegan_2.6-2         
## [91] reprex_2.0.1         digest_0.6.29        GPArotation_2022.4-1
## [94] munsell_0.5.0        bslib_0.3.1

#OSF
if (F) {
  library(osfr)
  #settings
  #you need to set up a personal token
  #good idea is to then place it somewhere safe for reuse
  osf_auth(read_lines("~/.config/osf_token"))
  
  #the project we will use
  osf_proj = osf_retrieve_node("https://osf.io/urx8f/")
  
  #upload all files in project
  #overwrite existing (versioning)
  osf_upload(osf_proj,
             path = c("notebook.html", "notebook.Rmd", "figs", "data", "sessions_info.txt"),
             conflicts = "overwrite")
}