all_data_irt_march_14
Bria Long
2023-03-14
Setup
library(tidyverse)
library(here)
library(lubridate)
library(ggthemes)
library(langcog)
library(mirt)
library(knitr)pilot_data_filtered <- read_csv(file = here::here('data/preprocessed_data/all_preprocessed_data.csv')) %>%
mutate(word1 = str_replace(word1, ' ', '.')) %>%
mutate(word2 = str_replace(word2, ' ', '.')) %>%
mutate(item_pair = paste0(word1,'_',word2))d_wide_all<- pilot_data_filtered %>%
ungroup() %>%
select(sub_id, item_pair, correct) %>%
arrange(item_pair) %>%
ungroup() %>%
pivot_wider(names_from=item_pair, values_from=correct, values_fn = ~mean(.x)) %>%
ungroup()
d_mat_all <- d_wide_all %>%
select(-sub_id) %>%
data.frame %>%
data.matrix
rownames(d_mat_all) <- d_wide_all$sub_idIterative 2PL IRT model with all data
With guess rate of 0.5 Removes items that have slopes <.7
outliers <- TRUE
maxiter <- 20
iteration <- 0
df_good <- d_mat_all
aminmax <- c(.7, Inf) # Keep items with positive slopes over .9
# Model priors specified in loop
while (outliers > 0 & iteration<maxiter){
iteration <- iteration + 1;
start.dim <- dim(df_good)[2]-1
mm = (
'F = 1-%d,
PRIOR = (1-%d, a1, norm, .2, 1),
PRIOR = (1-%d, d, norm, 0, 2)'
)
mm = mirt.model(sprintf(mm,start.dim,start.dim,start.dim))
m <- mirt(df_good, model = mm,itemtype = '2PL',guess=0.5) # 2AFC. Guess Rate = 0.5
co <- coef(m,simplify=TRUE, IRTpars = FALSE) # Get coeeficients
co <- tibble::rownames_to_column(as.data.frame(co$items),'words')
ggplot(co, aes(a1, d)) + geom_point(size=3)
# ggsave(sprintf('2PL-ModelParams_%d.png',iteration))
# Remove items with low or extreme slope and refit
df_good <- df_good[,which(co$a1>aminmax[1] & co$a1<aminmax[2])]
end.dim <- dim(df_good)[2]-1
outliers <- sum(!(co$a1>aminmax[1] & co$a1<aminmax[2]))
print(sprintf('2PL ITERATION %d. STARTED WITH %d ITEMS. %d OUTLIERS REMOVED. %d ITEMS RETAINED.',iteration,start.dim,outliers,end.dim))
}##
Iteration: 1, Log-Lik: -56576.090, Max-Change: 19.79992
Iteration: 2, Log-Lik: -43505.654, Max-Change: 10.32434
Iteration: 3, Log-Lik: -42380.588, Max-Change: 4.02271
Iteration: 4, Log-Lik: -42164.092, Max-Change: 2.13244
Iteration: 5, Log-Lik: -42106.750, Max-Change: 0.47059
Iteration: 6, Log-Lik: -42084.497, Max-Change: 0.10578
Iteration: 7, Log-Lik: -42074.445, Max-Change: 0.08024
Iteration: 8, Log-Lik: -42069.250, Max-Change: 0.06239
Iteration: 9, Log-Lik: -42066.279, Max-Change: 0.04749
Iteration: 10, Log-Lik: -42064.519, Max-Change: 0.03698
Iteration: 11, Log-Lik: -42063.458, Max-Change: 0.02859
Iteration: 12, Log-Lik: -42062.814, Max-Change: 0.02243
Iteration: 13, Log-Lik: -42061.855, Max-Change: 0.00552
Iteration: 14, Log-Lik: -42061.828, Max-Change: 0.00377
Iteration: 15, Log-Lik: -42061.814, Max-Change: 0.00319
Iteration: 16, Log-Lik: -42061.791, Max-Change: 0.00461
Iteration: 17, Log-Lik: -42061.789, Max-Change: 0.00175
Iteration: 18, Log-Lik: -42061.789, Max-Change: 0.00080
Iteration: 19, Log-Lik: -42061.788, Max-Change: 0.00038
Iteration: 20, Log-Lik: -42061.788, Max-Change: 0.00037
Iteration: 21, Log-Lik: -42061.788, Max-Change: 0.00037
Iteration: 22, Log-Lik: -42061.787, Max-Change: 0.00163
Iteration: 23, Log-Lik: -42061.787, Max-Change: 0.00116
Iteration: 24, Log-Lik: -42061.787, Max-Change: 0.00087
Iteration: 25, Log-Lik: -42061.787, Max-Change: 0.00028
Iteration: 26, Log-Lik: -42061.787, Max-Change: 0.00027
Iteration: 27, Log-Lik: -42061.787, Max-Change: 0.00133
Iteration: 28, Log-Lik: -42061.787, Max-Change: 0.00113
Iteration: 29, Log-Lik: -42061.787, Max-Change: 0.00087
Iteration: 30, Log-Lik: -42061.787, Max-Change: 0.00066
Iteration: 31, Log-Lik: -42061.787, Max-Change: 0.00022
Iteration: 32, Log-Lik: -42061.787, Max-Change: 0.00106
Iteration: 33, Log-Lik: -42061.787, Max-Change: 0.00080
Iteration: 34, Log-Lik: -42061.787, Max-Change: 0.00018
Iteration: 35, Log-Lik: -42061.787, Max-Change: 0.00018
Iteration: 36, Log-Lik: -42061.787, Max-Change: 0.00087
Iteration: 37, Log-Lik: -42061.787, Max-Change: 0.00062
Iteration: 38, Log-Lik: -42061.787, Max-Change: 0.00047
Iteration: 39, Log-Lik: -42061.787, Max-Change: 0.00036
Iteration: 40, Log-Lik: -42061.787, Max-Change: 0.00014
Iteration: 41, Log-Lik: -42061.787, Max-Change: 0.00069
Iteration: 42, Log-Lik: -42061.787, Max-Change: 0.00040
Iteration: 43, Log-Lik: -42061.787, Max-Change: 0.00012
Iteration: 44, Log-Lik: -42061.787, Max-Change: 0.00058
Iteration: 45, Log-Lik: -42061.787, Max-Change: 0.00040
Iteration: 46, Log-Lik: -42061.787, Max-Change: 0.00010
Iteration: 47, Log-Lik: -42061.787, Max-Change: 0.00049
Iteration: 48, Log-Lik: -42061.787, Max-Change: 0.00025
Iteration: 49, Log-Lik: -42061.787, Max-Change: 0.00008
## [1] "2PL ITERATION 1. STARTED WITH 392 ITEMS. 77 OUTLIERS REMOVED. 315 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -45533.039, Max-Change: 14.34072
Iteration: 2, Log-Lik: -34411.410, Max-Change: 6.52685
Iteration: 3, Log-Lik: -33395.206, Max-Change: 4.59254
Iteration: 4, Log-Lik: -33190.415, Max-Change: 1.07201
Iteration: 5, Log-Lik: -33135.889, Max-Change: 0.18865
Iteration: 6, Log-Lik: -33114.669, Max-Change: 0.10683
Iteration: 7, Log-Lik: -33103.998, Max-Change: 0.08372
Iteration: 8, Log-Lik: -33098.133, Max-Change: 0.06558
Iteration: 9, Log-Lik: -33094.706, Max-Change: 0.05089
Iteration: 10, Log-Lik: -33092.665, Max-Change: 0.03964
Iteration: 11, Log-Lik: -33091.441, Max-Change: 0.03064
Iteration: 12, Log-Lik: -33090.701, Max-Change: 0.02401
Iteration: 13, Log-Lik: -33089.599, Max-Change: 0.00651
Iteration: 14, Log-Lik: -33089.583, Max-Change: 0.00338
Iteration: 15, Log-Lik: -33089.574, Max-Change: 0.00215
Iteration: 16, Log-Lik: -33089.566, Max-Change: 0.00164
Iteration: 17, Log-Lik: -33089.563, Max-Change: 0.00135
Iteration: 18, Log-Lik: -33089.562, Max-Change: 0.00113
Iteration: 19, Log-Lik: -33089.559, Max-Change: 0.00077
Iteration: 20, Log-Lik: -33089.559, Max-Change: 0.00042
Iteration: 21, Log-Lik: -33089.559, Max-Change: 0.00023
Iteration: 22, Log-Lik: -33089.559, Max-Change: 0.00049
Iteration: 23, Log-Lik: -33089.559, Max-Change: 0.00040
Iteration: 24, Log-Lik: -33089.559, Max-Change: 0.00022
Iteration: 25, Log-Lik: -33089.559, Max-Change: 0.00032
Iteration: 26, Log-Lik: -33089.559, Max-Change: 0.00025
Iteration: 27, Log-Lik: -33089.559, Max-Change: 0.00014
Iteration: 28, Log-Lik: -33089.559, Max-Change: 0.00019
Iteration: 29, Log-Lik: -33089.559, Max-Change: 0.00023
Iteration: 30, Log-Lik: -33089.559, Max-Change: 0.00013
Iteration: 31, Log-Lik: -33089.559, Max-Change: 0.00004
## [1] "2PL ITERATION 2. STARTED WITH 315 ITEMS. 2 OUTLIERS REMOVED. 313 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -45268.116, Max-Change: 14.28993
Iteration: 2, Log-Lik: -34194.024, Max-Change: 6.56276
Iteration: 3, Log-Lik: -33214.664, Max-Change: 4.20871
Iteration: 4, Log-Lik: -33008.581, Max-Change: 1.37019
Iteration: 5, Log-Lik: -32950.802, Max-Change: 0.19505
Iteration: 6, Log-Lik: -32928.749, Max-Change: 0.11032
Iteration: 7, Log-Lik: -32917.666, Max-Change: 0.08567
Iteration: 8, Log-Lik: -32911.590, Max-Change: 0.06696
Iteration: 9, Log-Lik: -32908.044, Max-Change: 0.05190
Iteration: 10, Log-Lik: -32905.934, Max-Change: 0.04049
Iteration: 11, Log-Lik: -32904.669, Max-Change: 0.03113
Iteration: 12, Log-Lik: -32903.906, Max-Change: 0.02441
Iteration: 13, Log-Lik: -32902.771, Max-Change: 0.00664
Iteration: 14, Log-Lik: -32902.755, Max-Change: 0.00347
Iteration: 15, Log-Lik: -32902.746, Max-Change: 0.00211
Iteration: 16, Log-Lik: -32902.738, Max-Change: 0.00171
Iteration: 17, Log-Lik: -32902.735, Max-Change: 0.00141
Iteration: 18, Log-Lik: -32902.734, Max-Change: 0.00119
Iteration: 19, Log-Lik: -32902.730, Max-Change: 0.00090
Iteration: 20, Log-Lik: -32902.730, Max-Change: 0.00049
Iteration: 21, Log-Lik: -32902.730, Max-Change: 0.00028
Iteration: 22, Log-Lik: -32902.730, Max-Change: 0.00052
Iteration: 23, Log-Lik: -32902.730, Max-Change: 0.00044
Iteration: 24, Log-Lik: -32902.730, Max-Change: 0.00025
Iteration: 25, Log-Lik: -32902.730, Max-Change: 0.00034
Iteration: 26, Log-Lik: -32902.730, Max-Change: 0.00025
Iteration: 27, Log-Lik: -32902.730, Max-Change: 0.00015
Iteration: 28, Log-Lik: -32902.730, Max-Change: 0.00020
Iteration: 29, Log-Lik: -32902.730, Max-Change: 0.00019
Iteration: 30, Log-Lik: -32902.730, Max-Change: 0.00011
Iteration: 31, Log-Lik: -32902.730, Max-Change: 0.00015
Iteration: 32, Log-Lik: -32902.730, Max-Change: 0.00021
Iteration: 33, Log-Lik: -32902.730, Max-Change: 0.00012
Iteration: 34, Log-Lik: -32902.730, Max-Change: 0.00005
## [1] "2PL ITERATION 3. STARTED WITH 313 ITEMS. 1 OUTLIERS REMOVED. 312 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -45166.577, Max-Change: 14.26319
Iteration: 2, Log-Lik: -34125.901, Max-Change: 6.38952
Iteration: 3, Log-Lik: -33158.924, Max-Change: 4.72414
Iteration: 4, Log-Lik: -32951.540, Max-Change: 0.94181
Iteration: 5, Log-Lik: -32899.472, Max-Change: 0.19987
Iteration: 6, Log-Lik: -32878.482, Max-Change: 0.10925
Iteration: 7, Log-Lik: -32867.910, Max-Change: 0.08422
Iteration: 8, Log-Lik: -32862.102, Max-Change: 0.06570
Iteration: 9, Log-Lik: -32858.711, Max-Change: 0.05085
Iteration: 10, Log-Lik: -32856.695, Max-Change: 0.03953
Iteration: 11, Log-Lik: -32855.486, Max-Change: 0.03054
Iteration: 12, Log-Lik: -32854.757, Max-Change: 0.02392
Iteration: 13, Log-Lik: -32853.675, Max-Change: 0.00650
Iteration: 14, Log-Lik: -32853.659, Max-Change: 0.00318
Iteration: 15, Log-Lik: -32853.650, Max-Change: 0.00213
Iteration: 16, Log-Lik: -32853.640, Max-Change: 0.00151
Iteration: 17, Log-Lik: -32853.638, Max-Change: 0.00124
Iteration: 18, Log-Lik: -32853.637, Max-Change: 0.00132
Iteration: 19, Log-Lik: -32853.637, Max-Change: 0.00053
Iteration: 20, Log-Lik: -32853.636, Max-Change: 0.00046
Iteration: 21, Log-Lik: -32853.636, Max-Change: 0.00041
Iteration: 22, Log-Lik: -32853.635, Max-Change: 0.00082
Iteration: 23, Log-Lik: -32853.635, Max-Change: 0.00045
Iteration: 24, Log-Lik: -32853.635, Max-Change: 0.00152
Iteration: 25, Log-Lik: -32853.635, Max-Change: 0.00223
Iteration: 26, Log-Lik: -32853.635, Max-Change: 0.00132
Iteration: 27, Log-Lik: -32853.635, Max-Change: 0.00077
Iteration: 28, Log-Lik: -32853.635, Max-Change: 0.00026
Iteration: 29, Log-Lik: -32853.635, Max-Change: 0.00016
Iteration: 30, Log-Lik: -32853.635, Max-Change: 0.00044
Iteration: 31, Log-Lik: -32853.635, Max-Change: 0.00078
Iteration: 32, Log-Lik: -32853.635, Max-Change: 0.00045
Iteration: 33, Log-Lik: -32853.635, Max-Change: 0.00027
Iteration: 34, Log-Lik: -32853.635, Max-Change: 0.00009
## [1] "2PL ITERATION 4. STARTED WITH 312 ITEMS. 1 OUTLIERS REMOVED. 311 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -45097.534, Max-Change: 14.26793
Iteration: 2, Log-Lik: -34052.958, Max-Change: 6.45949
Iteration: 3, Log-Lik: -33084.504, Max-Change: 5.46831
Iteration: 4, Log-Lik: -32903.522, Max-Change: 0.49257
Iteration: 5, Log-Lik: -32834.266, Max-Change: 0.18552
Iteration: 6, Log-Lik: -32809.106, Max-Change: 0.11158
Iteration: 7, Log-Lik: -32796.886, Max-Change: 0.08827
Iteration: 8, Log-Lik: -32790.305, Max-Change: 0.06942
Iteration: 9, Log-Lik: -32786.489, Max-Change: 0.05385
Iteration: 10, Log-Lik: -32784.227, Max-Change: 0.04200
Iteration: 11, Log-Lik: -32782.874, Max-Change: 0.03227
Iteration: 12, Log-Lik: -32782.060, Max-Change: 0.02530
Iteration: 13, Log-Lik: -32780.856, Max-Change: 0.00673
Iteration: 14, Log-Lik: -32780.838, Max-Change: 0.00360
Iteration: 15, Log-Lik: -32780.828, Max-Change: 0.00218
Iteration: 16, Log-Lik: -32780.820, Max-Change: 0.00177
Iteration: 17, Log-Lik: -32780.818, Max-Change: 0.00146
Iteration: 18, Log-Lik: -32780.816, Max-Change: 0.00123
Iteration: 19, Log-Lik: -32780.812, Max-Change: 0.00093
Iteration: 20, Log-Lik: -32780.812, Max-Change: 0.00050
Iteration: 21, Log-Lik: -32780.812, Max-Change: 0.00029
Iteration: 22, Log-Lik: -32780.812, Max-Change: 0.00054
Iteration: 23, Log-Lik: -32780.812, Max-Change: 0.00047
Iteration: 24, Log-Lik: -32780.812, Max-Change: 0.00027
Iteration: 25, Log-Lik: -32780.812, Max-Change: 0.00036
Iteration: 26, Log-Lik: -32780.812, Max-Change: 0.00029
Iteration: 27, Log-Lik: -32780.812, Max-Change: 0.00017
Iteration: 28, Log-Lik: -32780.812, Max-Change: 0.00021
Iteration: 29, Log-Lik: -32780.812, Max-Change: 0.00026
Iteration: 30, Log-Lik: -32780.812, Max-Change: 0.00015
Iteration: 31, Log-Lik: -32780.812, Max-Change: 0.00005
## [1] "2PL ITERATION 5. STARTED WITH 311 ITEMS. 1 OUTLIERS REMOVED. 310 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -45034.012, Max-Change: 14.22868
Iteration: 2, Log-Lik: -34025.133, Max-Change: 6.43184
Iteration: 3, Log-Lik: -33038.876, Max-Change: 4.12162
Iteration: 4, Log-Lik: -32830.431, Max-Change: 1.52145
Iteration: 5, Log-Lik: -32772.626, Max-Change: 0.19167
Iteration: 6, Log-Lik: -32750.933, Max-Change: 0.10944
Iteration: 7, Log-Lik: -32740.106, Max-Change: 0.08493
Iteration: 8, Log-Lik: -32734.203, Max-Change: 0.06633
Iteration: 9, Log-Lik: -32730.769, Max-Change: 0.05131
Iteration: 10, Log-Lik: -32728.732, Max-Change: 0.03983
Iteration: 11, Log-Lik: -32727.515, Max-Change: 0.03078
Iteration: 12, Log-Lik: -32726.781, Max-Change: 0.02409
Iteration: 13, Log-Lik: -32725.697, Max-Change: 0.00654
Iteration: 14, Log-Lik: -32725.681, Max-Change: 0.00321
Iteration: 15, Log-Lik: -32725.672, Max-Change: 0.00215
Iteration: 16, Log-Lik: -32725.662, Max-Change: 0.00153
Iteration: 17, Log-Lik: -32725.660, Max-Change: 0.00125
Iteration: 18, Log-Lik: -32725.659, Max-Change: 0.00132
Iteration: 19, Log-Lik: -32725.658, Max-Change: 0.00053
Iteration: 20, Log-Lik: -32725.658, Max-Change: 0.00047
Iteration: 21, Log-Lik: -32725.657, Max-Change: 0.00041
Iteration: 22, Log-Lik: -32725.657, Max-Change: 0.00083
Iteration: 23, Log-Lik: -32725.657, Max-Change: 0.00045
Iteration: 24, Log-Lik: -32725.657, Max-Change: 0.00154
Iteration: 25, Log-Lik: -32725.656, Max-Change: 0.00227
Iteration: 26, Log-Lik: -32725.656, Max-Change: 0.00134
Iteration: 27, Log-Lik: -32725.656, Max-Change: 0.00078
Iteration: 28, Log-Lik: -32725.656, Max-Change: 0.00026
Iteration: 29, Log-Lik: -32725.656, Max-Change: 0.00017
Iteration: 30, Log-Lik: -32725.656, Max-Change: 0.00045
Iteration: 31, Log-Lik: -32725.656, Max-Change: 0.00080
Iteration: 32, Log-Lik: -32725.656, Max-Change: 0.00046
Iteration: 33, Log-Lik: -32725.656, Max-Change: 0.00028
Iteration: 34, Log-Lik: -32725.656, Max-Change: 0.00009
## [1] "2PL ITERATION 6. STARTED WITH 310 ITEMS. 1 OUTLIERS REMOVED. 309 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -45034.221, Max-Change: 14.13620
Iteration: 2, Log-Lik: -33945.875, Max-Change: 6.45192
Iteration: 3, Log-Lik: -32982.702, Max-Change: 5.51773
Iteration: 4, Log-Lik: -32802.754, Max-Change: 0.47821
Iteration: 5, Log-Lik: -32736.305, Max-Change: 0.17983
Iteration: 6, Log-Lik: -32712.416, Max-Change: 0.10692
Iteration: 7, Log-Lik: -32700.923, Max-Change: 0.08592
Iteration: 8, Log-Lik: -32694.729, Max-Change: 0.06694
Iteration: 9, Log-Lik: -32691.183, Max-Change: 0.07152
Iteration: 10, Log-Lik: -32689.085, Max-Change: 0.08870
Iteration: 11, Log-Lik: -32687.822, Max-Change: 0.21776
Iteration: 12, Log-Lik: -32687.022, Max-Change: 0.80753
Iteration: 13, Log-Lik: -32686.213, Max-Change: 5.05328
Iteration: 14, Log-Lik: -32676.275, Max-Change: 0.67228
Iteration: 15, Log-Lik: -32670.227, Max-Change: 0.04731
Iteration: 16, Log-Lik: -32670.113, Max-Change: 0.01785
Iteration: 17, Log-Lik: -32670.085, Max-Change: 0.00601
Iteration: 18, Log-Lik: -32670.073, Max-Change: 0.00256
Iteration: 19, Log-Lik: -32670.067, Max-Change: 0.00192
Iteration: 20, Log-Lik: -32670.063, Max-Change: 0.00162
Iteration: 21, Log-Lik: -32670.060, Max-Change: 0.00133
Iteration: 22, Log-Lik: -32670.055, Max-Change: 0.00078
Iteration: 23, Log-Lik: -32670.055, Max-Change: 0.00049
Iteration: 24, Log-Lik: -32670.055, Max-Change: 0.00028
Iteration: 25, Log-Lik: -32670.055, Max-Change: 0.00085
Iteration: 26, Log-Lik: -32670.055, Max-Change: 0.00096
Iteration: 27, Log-Lik: -32670.055, Max-Change: 0.00054
Iteration: 28, Log-Lik: -32670.055, Max-Change: 0.00019
Iteration: 29, Log-Lik: -32670.055, Max-Change: 0.00012
Iteration: 30, Log-Lik: -32670.055, Max-Change: 0.00042
Iteration: 31, Log-Lik: -32670.055, Max-Change: 0.00056
Iteration: 32, Log-Lik: -32670.055, Max-Change: 0.00033
Iteration: 33, Log-Lik: -32670.055, Max-Change: 0.00020
Iteration: 34, Log-Lik: -32670.055, Max-Change: 0.00007
## [1] "2PL ITERATION 7. STARTED WITH 309 ITEMS. 1 OUTLIERS REMOVED. 308 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -44825.487, Max-Change: 14.24352
Iteration: 2, Log-Lik: -33857.838, Max-Change: 6.41549
Iteration: 3, Log-Lik: -32898.186, Max-Change: 5.34328
Iteration: 4, Log-Lik: -32710.381, Max-Change: 0.43914
Iteration: 5, Log-Lik: -32639.407, Max-Change: 0.19417
Iteration: 6, Log-Lik: -32613.616, Max-Change: 0.11356
Iteration: 7, Log-Lik: -32601.157, Max-Change: 0.08977
Iteration: 8, Log-Lik: -32594.437, Max-Change: 0.06951
Iteration: 9, Log-Lik: -32590.589, Max-Change: 0.05401
Iteration: 10, Log-Lik: -32588.314, Max-Change: 0.04210
Iteration: 11, Log-Lik: -32586.955, Max-Change: 0.03232
Iteration: 12, Log-Lik: -32586.139, Max-Change: 0.02531
Iteration: 13, Log-Lik: -32584.937, Max-Change: 0.00688
Iteration: 14, Log-Lik: -32584.919, Max-Change: 0.00363
Iteration: 15, Log-Lik: -32584.909, Max-Change: 0.00220
Iteration: 16, Log-Lik: -32584.901, Max-Change: 0.00179
Iteration: 17, Log-Lik: -32584.898, Max-Change: 0.00147
Iteration: 18, Log-Lik: -32584.896, Max-Change: 0.00123
Iteration: 19, Log-Lik: -32584.892, Max-Change: 0.00090
Iteration: 20, Log-Lik: -32584.892, Max-Change: 0.00048
Iteration: 21, Log-Lik: -32584.892, Max-Change: 0.00028
Iteration: 22, Log-Lik: -32584.892, Max-Change: 0.00055
Iteration: 23, Log-Lik: -32584.892, Max-Change: 0.00057
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Iteration: 28, Log-Lik: -32584.892, Max-Change: 0.00010
Iteration: 29, Log-Lik: -32584.892, Max-Change: 0.00006
## [1] "2PL ITERATION 8. STARTED WITH 308 ITEMS. 2 OUTLIERS REMOVED. 306 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -44615.890, Max-Change: 14.18950
Iteration: 2, Log-Lik: -33612.461, Max-Change: 6.40974
Iteration: 3, Log-Lik: -32652.900, Max-Change: 4.08619
Iteration: 4, Log-Lik: -32448.724, Max-Change: 1.46209
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Iteration: 11, Log-Lik: -32346.907, Max-Change: 0.03020
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Iteration: 28, Log-Lik: -32345.138, Max-Change: 0.00014
Iteration: 29, Log-Lik: -32345.138, Max-Change: 0.00008
## [1] "2PL ITERATION 9. STARTED WITH 306 ITEMS. 1 OUTLIERS REMOVED. 305 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -44277.468, Max-Change: 14.37600
Iteration: 2, Log-Lik: -33408.728, Max-Change: 6.54879
Iteration: 3, Log-Lik: -32480.911, Max-Change: 4.58045
Iteration: 4, Log-Lik: -32272.028, Max-Change: 0.98148
Iteration: 5, Log-Lik: -32220.211, Max-Change: 0.19648
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Iteration: 9, Log-Lik: -32180.144, Max-Change: 0.05015
Iteration: 10, Log-Lik: -32178.215, Max-Change: 0.03887
Iteration: 11, Log-Lik: -32177.065, Max-Change: 0.02996
Iteration: 12, Log-Lik: -32176.375, Max-Change: 0.02339
Iteration: 13, Log-Lik: -32175.366, Max-Change: 0.00599
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Iteration: 27, Log-Lik: -32175.327, Max-Change: 0.00009
## [1] "2PL ITERATION 10. STARTED WITH 305 ITEMS. 1 OUTLIERS REMOVED. 304 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -44200.600, Max-Change: 14.36555
Iteration: 2, Log-Lik: -33398.884, Max-Change: 6.53100
Iteration: 3, Log-Lik: -32467.470, Max-Change: 5.28902
Iteration: 4, Log-Lik: -32284.420, Max-Change: 0.47666
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Iteration: 9, Log-Lik: -32164.213, Max-Change: 0.05282
Iteration: 10, Log-Lik: -32162.070, Max-Change: 0.04110
Iteration: 11, Log-Lik: -32160.795, Max-Change: 0.03150
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Iteration: 13, Log-Lik: -32158.916, Max-Change: 0.00620
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Iteration: 30, Log-Lik: -32158.875, Max-Change: 0.00018
Iteration: 31, Log-Lik: -32158.875, Max-Change: 0.00006
## [1] "2PL ITERATION 11. STARTED WITH 304 ITEMS. 1 OUTLIERS REMOVED. 303 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -44171.594, Max-Change: 14.49327
Iteration: 2, Log-Lik: -33353.687, Max-Change: 7.69781
Iteration: 3, Log-Lik: -32404.800, Max-Change: 4.86473
Iteration: 4, Log-Lik: -32236.212, Max-Change: 0.72904
Iteration: 5, Log-Lik: -32173.325, Max-Change: 0.19843
Iteration: 6, Log-Lik: -32149.987, Max-Change: 0.11048
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Iteration: 9, Log-Lik: -32129.229, Max-Change: 0.05159
Iteration: 10, Log-Lik: -32127.192, Max-Change: 0.03995
Iteration: 11, Log-Lik: -32125.983, Max-Change: 0.03075
Iteration: 12, Log-Lik: -32125.258, Max-Change: 0.02394
Iteration: 13, Log-Lik: -32124.207, Max-Change: 0.00635
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Iteration: 28, Log-Lik: -32124.166, Max-Change: 0.00013
Iteration: 29, Log-Lik: -32124.166, Max-Change: 0.00008
## [1] "2PL ITERATION 12. STARTED WITH 303 ITEMS. 1 OUTLIERS REMOVED. 302 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -44216.134, Max-Change: 37.64747
Iteration: 2, Log-Lik: -33269.401, Max-Change: 6.52420
Iteration: 3, Log-Lik: -32316.574, Max-Change: 4.54107
Iteration: 4, Log-Lik: -32136.606, Max-Change: 0.65019
Iteration: 5, Log-Lik: -32074.615, Max-Change: 0.17960
Iteration: 6, Log-Lik: -32051.276, Max-Change: 0.10989
Iteration: 7, Log-Lik: -32040.240, Max-Change: 0.08493
Iteration: 8, Log-Lik: -32034.433, Max-Change: 0.06596
Iteration: 9, Log-Lik: -32031.124, Max-Change: 0.05099
Iteration: 10, Log-Lik: -32029.191, Max-Change: 0.03888
Iteration: 11, Log-Lik: -32028.047, Max-Change: 0.03006
Iteration: 12, Log-Lik: -32027.364, Max-Change: 0.02342
Iteration: 13, Log-Lik: -32026.379, Max-Change: 0.00623
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Iteration: 25, Log-Lik: -32026.339, Max-Change: 0.00019
Iteration: 26, Log-Lik: -32026.339, Max-Change: 0.00011
Iteration: 27, Log-Lik: -32026.339, Max-Change: 0.00035
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Iteration: 29, Log-Lik: -32026.339, Max-Change: 0.00031
Iteration: 30, Log-Lik: -32026.339, Max-Change: 0.00019
Iteration: 31, Log-Lik: -32026.339, Max-Change: 0.00006
## [1] "2PL ITERATION 13. STARTED WITH 302 ITEMS. 2 OUTLIERS REMOVED. 300 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -43502.030, Max-Change: 14.63076
Iteration: 2, Log-Lik: -32796.879, Max-Change: 8.32444
Iteration: 3, Log-Lik: -31831.478, Max-Change: 5.11912
Iteration: 4, Log-Lik: -31668.117, Max-Change: 0.48556
Iteration: 5, Log-Lik: -31609.353, Max-Change: 0.16937
Iteration: 6, Log-Lik: -31587.009, Max-Change: 0.11159
Iteration: 7, Log-Lik: -31576.244, Max-Change: 0.08560
Iteration: 8, Log-Lik: -31570.503, Max-Change: 0.06601
Iteration: 9, Log-Lik: -31567.219, Max-Change: 0.05073
Iteration: 10, Log-Lik: -31565.298, Max-Change: 0.03979
Iteration: 11, Log-Lik: -31564.153, Max-Change: 0.03018
Iteration: 12, Log-Lik: -31563.474, Max-Change: 0.02322
Iteration: 13, Log-Lik: -31562.540, Max-Change: 0.00502
Iteration: 14, Log-Lik: -31562.517, Max-Change: 0.00431
Iteration: 15, Log-Lik: -31562.503, Max-Change: 0.00314
Iteration: 16, Log-Lik: -31562.488, Max-Change: 0.00264
Iteration: 17, Log-Lik: -31562.485, Max-Change: 0.00146
Iteration: 18, Log-Lik: -31562.483, Max-Change: 0.00119
Iteration: 19, Log-Lik: -31562.480, Max-Change: 0.00067
Iteration: 20, Log-Lik: -31562.480, Max-Change: 0.00037
Iteration: 21, Log-Lik: -31562.480, Max-Change: 0.00118
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Iteration: 26, Log-Lik: -31562.480, Max-Change: 0.00012
Iteration: 27, Log-Lik: -31562.480, Max-Change: 0.00008
## [1] "2PL ITERATION 14. STARTED WITH 300 ITEMS. 1 OUTLIERS REMOVED. 299 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -43305.621, Max-Change: 14.26489
Iteration: 2, Log-Lik: -32638.486, Max-Change: 7.54889
Iteration: 3, Log-Lik: -31731.980, Max-Change: 5.74525
Iteration: 4, Log-Lik: -31573.936, Max-Change: 0.35158
Iteration: 5, Log-Lik: -31513.249, Max-Change: 0.17291
Iteration: 6, Log-Lik: -31491.291, Max-Change: 0.10525
Iteration: 7, Log-Lik: -31480.998, Max-Change: 0.08248
Iteration: 8, Log-Lik: -31475.591, Max-Change: 0.06392
Iteration: 9, Log-Lik: -31472.518, Max-Change: 0.04943
Iteration: 10, Log-Lik: -31470.728, Max-Change: 0.03822
Iteration: 11, Log-Lik: -31469.663, Max-Change: 0.02900
Iteration: 12, Log-Lik: -31469.032, Max-Change: 0.02255
Iteration: 13, Log-Lik: -31468.158, Max-Change: 0.00466
Iteration: 14, Log-Lik: -31468.141, Max-Change: 0.00356
Iteration: 15, Log-Lik: -31468.130, Max-Change: 0.00228
Iteration: 16, Log-Lik: -31468.121, Max-Change: 0.00188
Iteration: 17, Log-Lik: -31468.118, Max-Change: 0.00152
Iteration: 18, Log-Lik: -31468.116, Max-Change: 0.00127
Iteration: 19, Log-Lik: -31468.112, Max-Change: 0.00082
Iteration: 20, Log-Lik: -31468.112, Max-Change: 0.00049
Iteration: 21, Log-Lik: -31468.112, Max-Change: 0.00029
Iteration: 22, Log-Lik: -31468.112, Max-Change: 0.00075
Iteration: 23, Log-Lik: -31468.112, Max-Change: 0.00101
Iteration: 24, Log-Lik: -31468.112, Max-Change: 0.00057
Iteration: 25, Log-Lik: -31468.112, Max-Change: 0.00019
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Iteration: 27, Log-Lik: -31468.112, Max-Change: 0.00077
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Iteration: 29, Log-Lik: -31468.112, Max-Change: 0.00015
Iteration: 30, Log-Lik: -31468.112, Max-Change: 0.00009
## [1] "2PL ITERATION 15. STARTED WITH 299 ITEMS. 1 OUTLIERS REMOVED. 298 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -43186.153, Max-Change: 14.48338
Iteration: 2, Log-Lik: -32628.740, Max-Change: 7.31660
Iteration: 3, Log-Lik: -31696.046, Max-Change: 4.51505
Iteration: 4, Log-Lik: -31517.105, Max-Change: 1.12462
Iteration: 5, Log-Lik: -31463.991, Max-Change: 0.18806
Iteration: 6, Log-Lik: -31444.002, Max-Change: 0.11346
Iteration: 7, Log-Lik: -31434.317, Max-Change: 0.08145
Iteration: 8, Log-Lik: -31429.130, Max-Change: 0.06293
Iteration: 9, Log-Lik: -31426.165, Max-Change: 0.04865
Iteration: 10, Log-Lik: -31424.432, Max-Change: 0.03762
Iteration: 11, Log-Lik: -31423.399, Max-Change: 0.02855
Iteration: 12, Log-Lik: -31422.788, Max-Change: 0.02220
Iteration: 13, Log-Lik: -31421.942, Max-Change: 0.00462
Iteration: 14, Log-Lik: -31421.925, Max-Change: 0.00352
Iteration: 15, Log-Lik: -31421.915, Max-Change: 0.00226
Iteration: 16, Log-Lik: -31421.906, Max-Change: 0.00186
Iteration: 17, Log-Lik: -31421.903, Max-Change: 0.00150
Iteration: 18, Log-Lik: -31421.901, Max-Change: 0.00125
Iteration: 19, Log-Lik: -31421.898, Max-Change: 0.00088
Iteration: 20, Log-Lik: -31421.898, Max-Change: 0.00053
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Iteration: 23, Log-Lik: -31421.897, Max-Change: 0.00091
Iteration: 24, Log-Lik: -31421.897, Max-Change: 0.00052
Iteration: 25, Log-Lik: -31421.897, Max-Change: 0.00016
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Iteration: 29, Log-Lik: -31421.897, Max-Change: 0.00014
Iteration: 30, Log-Lik: -31421.897, Max-Change: 0.00008
## [1] "2PL ITERATION 16. STARTED WITH 298 ITEMS. 1 OUTLIERS REMOVED. 297 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -43063.191, Max-Change: 14.58058
Iteration: 2, Log-Lik: -32569.929, Max-Change: 6.93401
Iteration: 3, Log-Lik: -31657.052, Max-Change: 5.26143
Iteration: 4, Log-Lik: -31487.208, Max-Change: 0.37763
Iteration: 5, Log-Lik: -31425.672, Max-Change: 0.18529
Iteration: 6, Log-Lik: -31403.035, Max-Change: 0.11664
Iteration: 7, Log-Lik: -31392.324, Max-Change: 0.08370
Iteration: 8, Log-Lik: -31386.672, Max-Change: 0.06514
Iteration: 9, Log-Lik: -31383.455, Max-Change: 0.05047
Iteration: 10, Log-Lik: -31381.582, Max-Change: 0.03905
Iteration: 11, Log-Lik: -31380.467, Max-Change: 0.02917
Iteration: 12, Log-Lik: -31379.816, Max-Change: 0.02328
Iteration: 13, Log-Lik: -31378.878, Max-Change: 0.00558
Iteration: 14, Log-Lik: -31378.866, Max-Change: 0.00212
Iteration: 15, Log-Lik: -31378.861, Max-Change: 0.00192
Iteration: 16, Log-Lik: -31378.852, Max-Change: 0.00153
Iteration: 17, Log-Lik: -31378.851, Max-Change: 0.00079
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Iteration: 30, Log-Lik: -31378.850, Max-Change: 0.00019
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Iteration: 36, Log-Lik: -31378.850, Max-Change: 0.00013
Iteration: 37, Log-Lik: -31378.850, Max-Change: 0.00005
## [1] "2PL ITERATION 17. STARTED WITH 297 ITEMS. 2 OUTLIERS REMOVED. 295 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -42928.172, Max-Change: 14.50660
Iteration: 2, Log-Lik: -32490.895, Max-Change: 6.35474
Iteration: 3, Log-Lik: -31585.405, Max-Change: 4.50152
Iteration: 4, Log-Lik: -31422.658, Max-Change: 1.28450
Iteration: 5, Log-Lik: -31372.383, Max-Change: 0.19192
Iteration: 6, Log-Lik: -31354.635, Max-Change: 0.10986
Iteration: 7, Log-Lik: -31346.029, Max-Change: 0.07722
Iteration: 8, Log-Lik: -31341.418, Max-Change: 0.05961
Iteration: 9, Log-Lik: -31338.791, Max-Change: 0.04597
Iteration: 10, Log-Lik: -31337.262, Max-Change: 0.03498
Iteration: 11, Log-Lik: -31336.362, Max-Change: 0.02706
Iteration: 12, Log-Lik: -31335.822, Max-Change: 0.02091
Iteration: 13, Log-Lik: -31335.090, Max-Change: 0.00470
Iteration: 14, Log-Lik: -31335.071, Max-Change: 0.00359
Iteration: 15, Log-Lik: -31335.061, Max-Change: 0.00241
Iteration: 16, Log-Lik: -31335.048, Max-Change: 0.00169
Iteration: 17, Log-Lik: -31335.046, Max-Change: 0.00140
Iteration: 18, Log-Lik: -31335.045, Max-Change: 0.00156
Iteration: 19, Log-Lik: -31335.044, Max-Change: 0.00060
Iteration: 20, Log-Lik: -31335.044, Max-Change: 0.00052
Iteration: 21, Log-Lik: -31335.043, Max-Change: 0.00045
Iteration: 22, Log-Lik: -31335.042, Max-Change: 0.00100
Iteration: 23, Log-Lik: -31335.042, Max-Change: 0.00054
Iteration: 24, Log-Lik: -31335.042, Max-Change: 0.00183
Iteration: 25, Log-Lik: -31335.042, Max-Change: 0.00276
Iteration: 26, Log-Lik: -31335.042, Max-Change: 0.00163
Iteration: 27, Log-Lik: -31335.042, Max-Change: 0.00096
Iteration: 28, Log-Lik: -31335.042, Max-Change: 0.00032
Iteration: 29, Log-Lik: -31335.042, Max-Change: 0.00020
Iteration: 30, Log-Lik: -31335.042, Max-Change: 0.00055
Iteration: 31, Log-Lik: -31335.042, Max-Change: 0.00098
Iteration: 32, Log-Lik: -31335.042, Max-Change: 0.00057
Iteration: 33, Log-Lik: -31335.042, Max-Change: 0.00034
Iteration: 34, Log-Lik: -31335.042, Max-Change: 0.00012
Iteration: 35, Log-Lik: -31335.042, Max-Change: 0.00007
## [1] "2PL ITERATION 18. STARTED WITH 295 ITEMS. 1 OUTLIERS REMOVED. 294 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -42971.881, Max-Change: 26.57850
Iteration: 2, Log-Lik: -32452.006, Max-Change: 6.13016
Iteration: 3, Log-Lik: -31545.626, Max-Change: 3.91902
Iteration: 4, Log-Lik: -31366.546, Max-Change: 1.27451
Iteration: 5, Log-Lik: -31311.972, Max-Change: 0.17905
Iteration: 6, Log-Lik: -31292.457, Max-Change: 0.10932
Iteration: 7, Log-Lik: -31283.345, Max-Change: 0.07765
Iteration: 8, Log-Lik: -31278.591, Max-Change: 0.05931
Iteration: 9, Log-Lik: -31275.920, Max-Change: 0.04560
Iteration: 10, Log-Lik: -31274.378, Max-Change: 0.03467
Iteration: 11, Log-Lik: -31273.476, Max-Change: 0.02680
Iteration: 12, Log-Lik: -31272.936, Max-Change: 0.02042
Iteration: 13, Log-Lik: -31272.222, Max-Change: 0.00510
Iteration: 14, Log-Lik: -31272.198, Max-Change: 0.00419
Iteration: 15, Log-Lik: -31272.184, Max-Change: 0.00332
Iteration: 16, Log-Lik: -31272.169, Max-Change: 0.00785
Iteration: 17, Log-Lik: -31272.166, Max-Change: 0.00128
Iteration: 18, Log-Lik: -31272.165, Max-Change: 0.00092
Iteration: 19, Log-Lik: -31272.164, Max-Change: 0.00067
Iteration: 20, Log-Lik: -31272.164, Max-Change: 0.00046
Iteration: 21, Log-Lik: -31272.163, Max-Change: 0.00039
Iteration: 22, Log-Lik: -31272.163, Max-Change: 0.00074
Iteration: 23, Log-Lik: -31272.163, Max-Change: 0.00048
Iteration: 24, Log-Lik: -31272.163, Max-Change: 0.00122
Iteration: 25, Log-Lik: -31272.162, Max-Change: 0.00214
Iteration: 26, Log-Lik: -31272.162, Max-Change: 0.00121
Iteration: 27, Log-Lik: -31272.162, Max-Change: 0.00070
Iteration: 28, Log-Lik: -31272.162, Max-Change: 0.00024
Iteration: 29, Log-Lik: -31272.162, Max-Change: 0.00064
Iteration: 30, Log-Lik: -31272.162, Max-Change: 0.00093
Iteration: 31, Log-Lik: -31272.162, Max-Change: 0.00032
Iteration: 32, Log-Lik: -31272.162, Max-Change: 0.00018
Iteration: 33, Log-Lik: -31272.162, Max-Change: 0.00011
Iteration: 34, Log-Lik: -31272.162, Max-Change: 0.00023
Iteration: 35, Log-Lik: -31272.162, Max-Change: 0.00010
Iteration: 36, Log-Lik: -31272.162, Max-Change: 0.00005
## [1] "2PL ITERATION 19. STARTED WITH 294 ITEMS. 2 OUTLIERS REMOVED. 292 ITEMS RETAINED."
##
Iteration: 1, Log-Lik: -42524.883, Max-Change: 14.62557
Iteration: 2, Log-Lik: -32113.248, Max-Change: 6.62731
Iteration: 3, Log-Lik: -31198.678, Max-Change: 5.58434
Iteration: 4, Log-Lik: -31032.983, Max-Change: 0.39426
Iteration: 5, Log-Lik: -30971.316, Max-Change: 0.18858
Iteration: 6, Log-Lik: -30949.555, Max-Change: 0.11783
Iteration: 7, Log-Lik: -30939.538, Max-Change: 0.07942
Iteration: 8, Log-Lik: -30934.337, Max-Change: 0.06170
Iteration: 9, Log-Lik: -30931.415, Max-Change: 0.04768
Iteration: 10, Log-Lik: -30929.728, Max-Change: 0.03677
Iteration: 11, Log-Lik: -30928.731, Max-Change: 0.02780
Iteration: 12, Log-Lik: -30928.146, Max-Change: 0.02148
Iteration: 13, Log-Lik: -30927.351, Max-Change: 0.00505
Iteration: 14, Log-Lik: -30927.334, Max-Change: 0.00347
Iteration: 15, Log-Lik: -30927.324, Max-Change: 0.00233
Iteration: 16, Log-Lik: -30927.314, Max-Change: 0.00177
Iteration: 17, Log-Lik: -30927.312, Max-Change: 0.00143
Iteration: 18, Log-Lik: -30927.310, Max-Change: 0.00117
Iteration: 19, Log-Lik: -30927.307, Max-Change: 0.00083
Iteration: 20, Log-Lik: -30927.307, Max-Change: 0.00049
Iteration: 21, Log-Lik: -30927.307, Max-Change: 0.00028
Iteration: 22, Log-Lik: -30927.307, Max-Change: 0.00066
Iteration: 23, Log-Lik: -30927.307, Max-Change: 0.00082
Iteration: 24, Log-Lik: -30927.307, Max-Change: 0.00044
Iteration: 25, Log-Lik: -30927.307, Max-Change: 0.00015
Iteration: 26, Log-Lik: -30927.307, Max-Change: 0.00047
Iteration: 27, Log-Lik: -30927.307, Max-Change: 0.00057
Iteration: 28, Log-Lik: -30927.307, Max-Change: 0.00022
Iteration: 29, Log-Lik: -30927.307, Max-Change: 0.00013
Iteration: 30, Log-Lik: -30927.307, Max-Change: 0.00007
## [1] "2PL ITERATION 20. STARTED WITH 292 ITEMS. 1 OUTLIERS REMOVED. 291 ITEMS RETAINED."Metadata merge and examination
school_meta <- read_csv(here::here('data/rocketship_data/cs01-metadata-age.csv')) %>%
as_tibble() %>%
select(pid, grade, age)sub_data_age_cleaned <- pilot_data_filtered %>%
filter(! cohort %in% c('school')) %>%
distinct(age, pid) %>%
mutate(age = str_replace(age, '\\+', '')) %>%
mutate(age = str_replace(age, 'Adult', '20')) %>%
mutate(age = as.numeric(age)) %>%
full_join(school_meta %>% select(pid,age))thetas_by_all_subs <- fscores(m) %>%
as_tibble() %>%
add_column(pid = d_wide_all$sub_id) %>%
rename(theta_2pl_all_data = `F`) %>%
left_join(sub_data_age_cleaned)thetas_by_age_all_data <- thetas_by_all_subs %>%
group_by(age) %>%
multi_boot_standard(col='theta_2pl_all_data') %>%
filter(!is.na(age))ggplot(data = thetas_by_all_subs, aes(x=age, y=theta_2pl_all_data, col=age)) +
geom_jitter(width=.2, alpha=.2) +
geom_smooth(method='lm', color='grey',alpha=.8) +
geom_pointrange(data=thetas_by_age_all_data,aes(x=age, y=mean, ymin=ci_lower, ymax =ci_upper), col='black', alpha=.5) +
theme_few() +
ylab('Theta estimates') +
xlab('Age') +
# facet_wrap(~model, nrow=2) +
theme(legend.position='none') +
theme(aspect.ratio=.75)
Break down by cohort.
ggplot(data = left_join(thetas_by_all_subs,
pilot_data_filtered |>
select(pid, cohort) |>
distinct()) ,
aes(x=age, y=theta_2pl_all_data, col=age)) +
geom_jitter(width=.2, alpha=.2) +
geom_smooth(method='lm', color='grey',alpha=.8) +
theme_few() +
ylab('Theta estimates') +
xlab('Age') +
# facet_wrap(~model, nrow=2) +
theme(legend.position='none') +
facet_wrap(~cohort)
Compare with raw scores.
ggplot(data = left_join(thetas_by_all_subs,
pilot_data_filtered |>
select(pid, cohort, correct) |>
group_by(pid, cohort) |>
summarise(correct = mean(correct))) ,
aes(x=age, y=correct, col=age)) +
geom_jitter(width=.2, alpha=.2) +
geom_smooth(method='lm', color='grey',alpha=.8) +
theme_few() +
geom_hline(yintercept = .5, lty = 2) +
ylab('Theta estimates') +
xlab('Age') +
theme(legend.position='none') +
facet_wrap(~cohort)
Now age to theta. Model is buying us some within-raw score
differentiation, and a little bit of grouping of low scores
vs. differentiation of high ones (curves). But not a ton of difference,
which is good.
ggplot(data = left_join(thetas_by_all_subs,
pilot_data_filtered |>
select(pid, cohort, correct) |>
group_by(pid, cohort) |>
summarise(correct = mean(correct))) ,
aes(x=correct, y=theta_2pl_all_data, col=age)) +
geom_jitter(alpha=.2) +
geom_smooth(color='grey',alpha=.8) +
theme_few() +
ylab('Theta estimates') +
xlab('Raw Score') +
theme(legend.position='none') +
facet_wrap(~cohort)
See which items were retained
Items by difficulty.
diffs_pruned <- co |>
mutate(slope = a1,
item_pair = words) |>
mutate(difficulty = -d) |>
select(item_pair, difficulty, a1) |>
arrange(-difficulty)
diffs_pruned |>
kable(digits = 2)| item_pair | difficulty | a1 |
|---|---|---|
| savor_toothbrushing | 3.04 | 1.12 |
| bobsled_sidecar | 2.99 | 2.39 |
| intersection_monastery | 2.85 | 1.03 |
| savor_to.smell | 2.79 | 1.03 |
| metronome_voltmeter | 2.55 | 0.99 |
| grate_crate | 2.52 | 0.97 |
| aversion_dull | 2.41 | 1.03 |
| mischievous_suprised | 2.40 | 1.02 |
| swordfish_catfish | 2.32 | 1.48 |
| bust_statue | 2.21 | 1.27 |
| pitcher_tumbleweed | 2.16 | 2.88 |
| triad_myriad | 2.13 | 0.85 |
| incensed_doubt | 2.07 | 1.04 |
| mischievous_headaches | 2.04 | 1.83 |
| convoy_library | 1.97 | 1.09 |
| aversion_delighted | 1.95 | 1.17 |
| percussion_accordion | 1.90 | 1.36 |
| colony_school | 1.87 | 1.10 |
| coaster_painting | 1.87 | 2.15 |
| posterior_inferior | 1.81 | 0.81 |
| thermos_oilcan | 1.77 | 2.60 |
| figurehead_angel | 1.65 | 1.21 |
| corset_harness | 1.59 | 2.38 |
| freezer_cooler | 1.52 | 1.82 |
| resuscitation_breathing | 1.52 | 0.85 |
| aloe_bracket | 1.50 | 2.78 |
| sauerkraut_potpourri | 1.49 | 1.71 |
| pitcher_batter | 1.49 | 2.84 |
| cheese_butter | 1.38 | 1.94 |
| flan_amplifier | 1.34 | 2.40 |
| habit_diving.helmet | 1.33 | 1.14 |
| scrabble_whisk | 1.30 | 2.64 |
| posterior_lateral | 1.30 | 0.91 |
| flan_fuse | 1.28 | 2.03 |
| mulch_clarinet | 1.23 | 2.41 |
| scaffolding_satellite | 1.23 | 3.09 |
| figurehead_hero.image | 1.19 | 1.05 |
| ecstatic_to.sleep | 1.13 | 1.52 |
| stew_soup | 1.10 | 1.77 |
| steam_blacksmith | 1.05 | 1.10 |
| metronome_electricity.meter | 1.04 | 0.94 |
| rosette_rose.ball | 1.02 | 1.13 |
| slope_gap | 1.00 | 1.10 |
| parsley_basil | 0.84 | 1.11 |
| habit_mail | 0.82 | 0.88 |
| intersection_avenue | 0.79 | 1.42 |
| preserve_grilling | 0.71 | 1.22 |
| bouquet_centerpiece | 0.69 | 2.64 |
| sedentary_tripod | 0.62 | 0.76 |
| preserve_peel | 0.55 | 0.97 |
| pajamas_pants | 0.50 | 0.85 |
| grate_reel | 0.50 | 2.28 |
| cymbal_kaleidoscope | 0.44 | 1.11 |
| prune_raisin | 0.43 | 0.95 |
| artifact_crystal | 0.40 | 2.06 |
| carousel_carriage | 0.38 | 1.23 |
| slope_sky | 0.35 | 1.00 |
| bouquet_bandanna | 0.32 | 2.27 |
| beret_chef.s.hat | 0.31 | 0.79 |
| gutter_filter | 0.29 | 1.77 |
| sedentary_proposal | 0.27 | 0.97 |
| rickety_dusk | 0.25 | 1.71 |
| cloak_hood | 0.18 | 0.79 |
| preserve_Heels | 0.17 | 0.96 |
| rickety_skyscraper | 0.14 | 1.19 |
| stump_log | 0.14 | 1.95 |
| scrabble_poker | 0.14 | 2.05 |
| bobsled_dip | 0.03 | 1.65 |
| ecstatic_tired | 0.00 | 1.26 |
| pecan_peanut | -0.02 | 1.66 |
| clothespin_toothpick | -0.05 | 1.24 |
| sedentary_effort | -0.05 | 1.14 |
| convoy_provisions | -0.07 | 0.83 |
| tulip_rose | -0.11 | 1.43 |
| prism_radar | -0.13 | 2.53 |
| gondola_trolley | -0.15 | 0.97 |
| kimono_turntable | -0.21 | 1.85 |
| artichoke_leek | -0.28 | 0.95 |
| parsley_tiara | -0.28 | 2.08 |
| oatmeal_cereal | -0.34 | 0.96 |
| tapestry_backdrop | -0.34 | 1.00 |
| syringe_seismograph | -0.35 | 1.79 |
| tumble_applaud | -0.36 | 0.00 |
| saffron_cinnamon | -0.39 | 1.88 |
| scaffolding_veil | -0.39 | 1.87 |
| headdress_crown | -0.40 | 1.10 |
| posterior_frontal | -0.42 | 0.77 |
| cornbread_corn | -0.49 | 0.82 |
| steam_rust | -0.50 | 0.79 |
| antenna_stem | -0.55 | 1.84 |
| modem_baklava | -0.60 | 1.26 |
| mandolin_gourd | -0.60 | 1.35 |
| gourmet_archaeological | -0.63 | 1.56 |
| mandolin_mast | -0.64 | 1.78 |
| cloak_cinnamon | -0.67 | 1.81 |
| artifact_herringbone | -0.73 | 1.20 |
| modem_scanner | -0.73 | 1.01 |
| sorbet_tamale | -0.74 | 0.85 |
| corset_mantle | -0.75 | 1.47 |
| silverware_trophy | -0.75 | 1.70 |
| pistachio_taco | -0.76 | 1.65 |
| dumpling_meatball | -0.76 | 0.84 |
| kayak_pendulum | -0.78 | 1.72 |
| teapot_teacup | -0.81 | 1.05 |
| oil_gel | -0.81 | 1.00 |
| bandage_stretcher | -0.83 | 0.78 |
| kimono_cardigan | -0.87 | 1.44 |
| steam_pottery | -0.87 | 1.92 |
| prune_headrest | -0.89 | 1.48 |
| bulldozer_tractor | -0.91 | 1.20 |
| slope_flat | -0.94 | 0.86 |
| sorbet_palette | -0.94 | 1.00 |
| omelet_clay | -0.95 | 1.67 |
| caramel_amber | -0.97 | 0.85 |
| sandbag_sandpaper | -0.97 | 0.96 |
| syringe_vial | -0.97 | 1.38 |
| rosette_manhole.cover | -1.04 | 1.30 |
| foam_float | -1.07 | 2.04 |
| thermos_firewood | -1.11 | 2.16 |
| aloe_cactus | -1.12 | 1.44 |
| blower_burner | -1.13 | 1.04 |
| hoe_peg | -1.16 | 1.56 |
| foam_quilt | -1.17 | 1.03 |
| coaster_card | -1.18 | 1.46 |
| sauerkraut_dashboard | -1.18 | 1.10 |
| prism_subway | -1.20 | 1.63 |
| gourmet_surgical | -1.24 | 1.57 |
| latch_lock | -1.24 | 1.68 |
| beret_hat | -1.25 | 0.86 |
| saddle_handle | -1.27 | 1.88 |
| pecan_steak | -1.28 | 1.64 |
| scoop_sauce | -1.29 | 0.97 |
| seaweed_seafood | -1.33 | 1.04 |
| shredder_razor | -1.36 | 1.32 |
| saddle_figurine | -1.39 | 1.69 |
| pump_plug | -1.44 | 1.42 |
| headdress_poster | -1.45 | 1.26 |
| neck_shoulder | -1.46 | 1.07 |
| rickety_vacation.home | -1.47 | 0.89 |
| towel_blanket | -1.58 | 0.87 |
| stew_mixer | -1.59 | 2.09 |
| sloth_clam | -1.61 | 1.09 |
| swing_slide | -1.63 | 1.13 |
| stump_bookshelf | -1.63 | 2.20 |
| snail_worm | -1.67 | 1.18 |
| cassette_tape | -1.71 | 1.26 |
| neck_diaper | -1.73 | 0.90 |
| cork_jersey | -1.75 | 1.85 |
| hopscotch_chalk | -1.76 | 0.84 |
| hoe_dustpan | -1.77 | 0.88 |
| bark_skin | -1.78 | 1.92 |
| biscuit_column | -1.79 | 0.98 |
| fox_wolf | -1.82 | 0.76 |
| strap_sweater | -1.83 | 1.76 |
| artichoke_sunroof | -1.84 | 1.12 |
| conference_toast | -1.85 | 1.19 |
| puddle_bubble | -1.85 | 1.39 |
| stretcher_thermostat | -1.86 | 1.00 |
| conference_group.lesson | -1.87 | 1.14 |
| spinach_mint | -1.87 | 1.58 |
| gourmet_astronomical | -1.87 | 1.48 |
| bandage_bag.binder | -1.89 | 1.16 |
| gondola_clipboard | -1.92 | 0.89 |
| seagull_pigeon | -1.92 | 1.38 |
| teabag_tea | -1.92 | 1.24 |
| treasure_gift | -1.95 | 1.24 |
| shredder_padlock | -1.96 | 1.45 |
| tulip_glove | -1.96 | 1.83 |
| taillight_luggage | -1.97 | 1.12 |
| antenna_pinecone | -1.98 | 1.41 |
| cork_skateboard | -1.99 | 1.61 |
| gutter_almond | -2.00 | 1.84 |
| pistachio_avocado | -2.03 | 0.87 |
| screw_saw | -2.04 | 1.23 |
| puddle_baseball | -2.05 | 1.12 |
| koala_panda | -2.05 | 1.04 |
| latch_microwave | -2.08 | 1.84 |
| ship_boat | -2.11 | 1.53 |
| stretcher_drill | -2.12 | 1.78 |
| buffet_counter | -2.18 | 1.04 |
| pump_coat | -2.19 | 0.86 |
| squirrel_monkey | -2.20 | 0.72 |
| bark_thumb | -2.20 | 1.67 |
| hopscotch_funnel | -2.20 | 1.31 |
| silverware_garlic | -2.23 | 1.72 |
| sloth_donkey | -2.24 | 0.73 |
| hedgehog_iguana | -2.24 | 1.10 |
| bandage_mop | -2.26 | 0.89 |
| pajamas_cage | -2.27 | 0.78 |
| honey_puppet | -2.28 | 1.78 |
| squash_branch | -2.29 | 0.94 |
| fruitcake_fudge | -2.30 | 1.35 |
| papaya_hotplate | -2.31 | 1.83 |
| gazelle_tarantula | -2.32 | 1.48 |
| chandelier_pepperoni | -2.32 | 1.52 |
| barrel_shelf | -2.32 | 1.25 |
| sandbag_valve | -2.34 | 1.02 |
| fruitcake_dough | -2.38 | 1.16 |
| strap_staple | -2.38 | 1.06 |
| chat_mountaineering | -2.40 | 0.71 |
| cassette_book | -2.41 | 1.38 |
| artifact_honeycomb | -2.44 | 1.47 |
| trumpet_flute | -2.46 | 1.26 |
| otter_goose | -2.47 | 1.03 |
| barrel_bucket | -2.48 | 1.08 |
| chat_referee | -2.49 | 1.13 |
| candlestick_egg | -2.55 | 1.05 |
| caramel_olive | -2.57 | 1.03 |
| ski_ice | -2.58 | 1.04 |
| shower_soap | -2.59 | 1.44 |
| bulldozer_orange | -2.61 | 2.02 |
| coffee_vase | -2.61 | 1.02 |
| dumpling_rocket | -2.65 | 1.59 |
| hamster_rabbit | -2.66 | 1.30 |
| tapestry_leggings | -2.66 | 1.43 |
| map_ruby | -2.68 | 1.11 |
| carousel_dish | -2.69 | 1.33 |
| bamboo_yacht | -2.69 | 1.15 |
| fence_mask | -2.70 | 2.07 |
| horn_chin | -2.72 | 1.14 |
| blender_blind | -2.73 | 0.97 |
| bamboo_lumber | -2.75 | 1.18 |
| chat_horse.riding | -2.78 | 1.61 |
| towel_sausage | -2.81 | 1.35 |
| squirrel_eagle | -2.82 | 1.46 |
| clothespin_volleyball | -2.82 | 1.66 |
| carrot_phone | -2.83 | 1.09 |
| net_tee | -2.84 | 1.75 |
| telescope_tripod | -2.84 | 1.68 |
| spinach_buckle | -2.86 | 1.20 |
| spatula_lava | -2.86 | 1.81 |
| scoop_statue | -2.87 | 1.15 |
| oil_grain | -2.88 | 1.59 |
| coffee_drink | -2.92 | 1.11 |
| seagull_lobster | -2.98 | 1.33 |
| swing_foot | -2.98 | 1.48 |
| sink_toilet | -3.01 | 1.37 |
| shirt_uniform | -3.02 | 1.51 |
| shower_toe | -3.04 | 1.25 |
| map_marker | -3.05 | 1.23 |
| shirt_salad | -3.06 | 1.04 |
| rice_dice | -3.10 | 1.30 |
| locker_basket | -3.10 | 1.64 |
| hedgehog_owl | -3.13 | 1.42 |
| lollipop_doorbell | -3.13 | 0.99 |
| locker_cabinet | -3.13 | 0.86 |
| cake_refrigerator | -3.14 | 0.90 |
| teapot_brake | -3.16 | 1.24 |
| blender_mailbox | -3.16 | 1.22 |
| camp_to.steal | -3.17 | 1.62 |
| buffet_crib | -3.18 | 1.63 |
| fan_boulder | -3.19 | 1.34 |
| carrot_vegetable | -3.20 | 1.06 |
| teabag_fingerprint | -3.22 | 1.30 |
| milkshake_robot | -3.26 | 1.28 |
| trumpet_violin | -3.28 | 1.48 |
| fan_album | -3.28 | 1.19 |
| acorn_coconut | -3.29 | 1.47 |
| footbath_trough | -3.30 | 1.01 |
| seaweed_mousetrap | -3.33 | 1.56 |
| footbath_vest | -3.34 | 0.92 |
| fence_railing | -3.34 | 1.46 |
| honey_baby | -3.36 | 1.98 |
| sunflower_pineapple | -3.42 | 0.90 |
| potato_pot | -3.45 | 1.30 |
| oatmeal_collar | -3.46 | 1.26 |
| freezer_nest | -3.48 | 0.98 |
| swordfish_leopard | -3.51 | 1.82 |
| rice_box | -3.51 | 1.05 |
| telescope_windshield | -3.54 | 1.34 |
| hamster_tadpole | -3.54 | 1.72 |
| ski_suitcase | -3.60 | 1.97 |
| potato_glasses | -3.60 | 1.29 |
| cake_dessert | -3.61 | 1.13 |
| sprinkler_flower | -3.63 | 1.35 |
| net_domino | -3.68 | 1.78 |
| triangle_diamond | -3.69 | 1.24 |
| ship_nose | -3.69 | 0.96 |
| sunflower_rim | -3.70 | 0.99 |
| chandelier_lightbulb | -3.71 | 1.82 |
| snail_cow | -3.72 | 0.99 |
| acorn_key | -3.73 | 1.52 |
| cornbread_wreath | -3.74 | 1.49 |
| lollipop_candy | -3.82 | 1.74 |
| treasure_rope | -3.84 | 1.84 |
| cheese_mud | -3.86 | 1.29 |
| tongue_lipstick | -3.89 | 1.96 |
| marshmallow_dryer | -3.89 | 1.39 |
| tongue_envelope | -3.90 | 1.02 |
| sink_stair | -3.92 | 2.06 |
| pie_flashlight | -3.92 | 1.44 |
| triangle_lighter | -4.30 | 1.72 |
| elbow_bed | -4.37 | 1.69 |
Try some other models
Partially compensatory 2PL.
mm_c = (
'F = 1-%d,
PRIOR = (1-%d, a1, norm, .2, 1),
PRIOR = (1-%d, d, norm, 0, 2)'
)
m_pc <- mirt(df_good, itemtype = 'PC2PL', guess=0.5) # 2AFC. Guess Rate = 0.5##
Iteration: 1, Log-Lik: -35730.185, Max-Change: 4.24877
Iteration: 2, Log-Lik: -29809.076, Max-Change: 1.45308
Iteration: 3, Log-Lik: -29629.211, Max-Change: 1.13032
Iteration: 4, Log-Lik: -29578.517, Max-Change: 0.93007
Iteration: 5, Log-Lik: -29556.643, Max-Change: 0.83335
Iteration: 6, Log-Lik: -29544.768, Max-Change: 0.00638
Iteration: 7, Log-Lik: -29544.569, Max-Change: 0.00000co_pc <- coef(m_pc, simplify=TRUE) # Get coeeficients
co_pc <- tibble::rownames_to_column(as.data.frame(co_pc$items),'words')Prune items and check model for multi-AFC study
Get items with difficulty pairs
Get item info for rejoining
item_info_clip <- pilot_data_filtered %>%
filter(cohort == 'prolific') %>%
distinct(item_pair, wordPairing, cor) %>%
rename(wordPairingClip = wordPairing)Get item pc/responses overall
items_all_responses <- pilot_data_filtered %>%
group_by(item_pair, word1, word2) %>%
summarize(num_responses = length(correct), pc = mean(correct)) Add back in pc for sanity & and word pairing details
coefficients_pruned_items <- diffs_pruned %>%
left_join(items_all_responses) %>%
left_join(item_info_clip) %>%
mutate(wordPairingClip = replace_na(wordPairingClip, 'DAIVT'))items_with_matches <- coefficients_pruned_items %>%
group_by(word1) %>%
mutate(num_pairs_retains = length(unique(word2))) %>%
filter(num_pairs_retains>1)Model fitting
Refit a model with this subset of items
kept_items = items_with_matches$item_pair
d_wide_model_subset<- pilot_data_filtered %>%
ungroup() %>%
filter(item_pair %in% kept_items) %>%
select(sub_id, item_pair, correct) %>%
arrange(item_pair) %>%
ungroup() %>%
pivot_wider(names_from=item_pair, values_from=correct, values_fn = ~mean(.x)) %>%
ungroup()
d_mat_model_subset <- d_wide_model_subset %>%
select(-sub_id) %>%
data.frame %>%
data.matrix
rownames(d_mat_model_subset) <- d_wide_model_subset$sub_idFit a 2PL model to this subset
start.dim = length(colnames(d_mat_model_subset)) - 1
mm = (
'F = 1-%d,
PRIOR = (1-%d, a1, norm, .2, 1),
PRIOR = (1-%d, d, norm, 0, 2)'
)
mm = mirt.model(sprintf(mm,start.dim,start.dim,start.dim))
mod_2pl_priors_subset <- mirt::mirt(d_mat_model_subset, mm,
itemtype='2PL', guess=.5, upper=1,
verbose=FALSE)Get coefficients
co_sub <- coef(mod_2pl_priors_subset,simplify=TRUE, IRTpars = FALSE) # Get coeeficients
co_sub <- tibble::rownames_to_column(as.data.frame(co$items),'words')Look at thetas by sub
all_thetas_with_matched_subset <- fscores(mod_2pl_priors_subset) %>%
as_tibble() %>%
add_column(pid = d_wide_model_subset$sub_id) %>%
rename(theta_2pl_matched_data = `F`) %>%
left_join(sub_data_age_cleaned)thetas_by_age_matched_subset <- all_thetas_with_matched_subset %>%
group_by(age) %>%
multi_boot_standard(col='theta_2pl_matched_data') %>%
filter(!is.na(age))ggplot(data = all_thetas_with_matched_subset, aes(x=age, y=theta_2pl_matched_data, col=age)) +
geom_jitter(width=.2, alpha=.2) +
geom_smooth(method='lm', color='grey',alpha=.8) +
geom_pointrange(data=thetas_by_age_matched_subset,aes(x=age, y=mean, ymin=ci_lower, ymax =ci_upper), col='black', alpha=.5) +
theme_few() +
ylab('Theta estimates') +
xlab('Age') +
# facet_wrap(~model, nrow=2) +
theme(legend.position='none') +
theme(aspect.ratio=.75)
Show items by difficulty
coefficients_pruned_items <- co %>%
mutate(slope = a1, item_pair = words) %>%
mutate(difficulty = -d) %>%
arrange(-difficulty) Get item info for rejoining
item_info_clip <- pilot_data_filtered %>%
filter(cohort == 'prolific') %>%
distinct(item_pair, wordPairing, cor) %>%
rename(wordPairingClip = wordPairing)Get item pc/responses overall
items_all_responses <- pilot_data_filtered %>%
group_by(item_pair, word1, word2) %>%
summarize(num_responses = length(correct), pc = mean(correct)) Add back in pc for sanity & and word pairing details
coefficients_pruned_items <- coefficients_pruned_items %>%
left_join(items_all_responses) %>%
left_join(item_info_clip) %>%
mutate(wordPairingClip = replace_na(wordPairingClip, 'DAIVT'))Examine difficulties
coef_pairs <- filter(coefficients_pruned_items,
wordPairingClip %in% c("easy","hard")) |>
mutate(word1 = fct_reorder(word1, difficulty, .desc=TRUE))
ggplot(data = coef_pairs,
aes(x=difficulty, y=word1, col = wordPairingClip)) +
geom_point(alpha=.5) +
geom_line(aes(group = word1), alpha = .3, col = "gray") +
theme_few(base_size=10) +
xlab("IRT difficulty") +
ylab("IRT discriminability (slope)") 
coefficients_pruned_items %>%
filter(wordPairingClip %in% c('easy','hard')) %>%
select(word1, difficulty, wordPairingClip) %>%
pivot_wider(values_from = difficulty, names_from=wordPairingClip) %>%
mutate(diff = hard - easy) %>%
arrange(-diff) %>%
kable(digits = 2)| word1 | hard | easy | diff |
|---|---|---|---|
| swordfish | 2.32 | -3.51 | 5.83 |
| cheese | 1.38 | -3.86 | 5.24 |
| freezer | 1.52 | -3.48 | 5.01 |
| cornbread | -0.49 | -3.74 | 3.25 |
| oatmeal | -0.34 | -3.46 | 3.12 |
| carousel | 0.38 | -2.69 | 3.06 |
| bobsled | 2.99 | 0.03 | 2.96 |
| thermos | 1.77 | -1.11 | 2.89 |
| clothespin | -0.05 | -2.82 | 2.77 |
| pajamas | 0.50 | -2.27 | 2.77 |
| stew | 1.10 | -1.59 | 2.69 |
| sauerkraut | 1.49 | -1.18 | 2.67 |
| teapot | -0.81 | -3.16 | 2.35 |
| corset | 1.59 | -0.75 | 2.34 |
| tapestry | -0.34 | -2.66 | 2.32 |
| gutter | 0.29 | -2.00 | 2.29 |
| oil | -0.81 | -2.88 | 2.07 |
| snail | -1.67 | -3.72 | 2.04 |
| grate | 2.52 | 0.50 | 2.03 |
| seaweed | -1.33 | -3.33 | 2.01 |
| treasure | -1.95 | -3.84 | 1.90 |
| dumpling | -0.76 | -2.65 | 1.89 |
| tulip | -0.11 | -1.96 | 1.85 |
| stump | 0.14 | -1.63 | 1.77 |
| gondola | -0.15 | -1.92 | 1.76 |
| bulldozer | -0.91 | -2.61 | 1.70 |
| scaffolding | 1.23 | -0.39 | 1.62 |
| caramel | -0.97 | -2.57 | 1.60 |
| ship | -2.11 | -3.69 | 1.58 |
| scoop | -1.29 | -2.87 | 1.58 |
| artichoke | -0.28 | -1.84 | 1.56 |
| silverware | -0.75 | -2.23 | 1.47 |
| antenna | -0.55 | -1.98 | 1.44 |
| sandbag | -0.97 | -2.34 | 1.37 |
| swing | -1.63 | -2.98 | 1.35 |
| prune | 0.43 | -0.89 | 1.32 |
| teabag | -1.92 | -3.22 | 1.30 |
| pecan | -0.02 | -1.28 | 1.27 |
| towel | -1.58 | -2.81 | 1.23 |
| parsley | 0.84 | -0.28 | 1.12 |
| prism | -0.13 | -1.20 | 1.06 |
| seagull | -1.92 | -2.98 | 1.06 |
| headdress | -0.40 | -1.45 | 1.05 |
| ski | -2.58 | -3.60 | 1.02 |
| buffet | -2.18 | -3.18 | 1.00 |
| spinach | -1.87 | -2.86 | 0.99 |
| sink | -3.01 | -3.92 | 0.91 |
| hamster | -2.66 | -3.54 | 0.88 |
| cloak | 0.18 | -0.67 | 0.85 |
| net | -2.84 | -3.68 | 0.84 |
| latch | -1.24 | -2.08 | 0.84 |
| trumpet | -2.46 | -3.28 | 0.82 |
| pump | -1.44 | -2.19 | 0.75 |
| cassette | -1.71 | -2.41 | 0.71 |
| telescope | -2.84 | -3.54 | 0.70 |
| squirrel | -2.20 | -2.82 | 0.62 |
| hoe | -1.16 | -1.77 | 0.61 |
| triangle | -3.69 | -4.30 | 0.60 |
| shredder | -1.36 | -1.96 | 0.60 |
| hopscotch | -1.76 | -2.20 | 0.45 |
| shower | -2.59 | -3.04 | 0.45 |
| acorn | -3.29 | -3.73 | 0.44 |
| blender | -2.73 | -3.16 | 0.43 |
| bark | -1.78 | -2.20 | 0.42 |
| rice | -3.10 | -3.51 | 0.41 |
| bouquet | 0.69 | 0.32 | 0.37 |
| sunflower | -3.42 | -3.70 | 0.28 |
| neck | -1.46 | -1.73 | 0.27 |
| cork | -1.75 | -1.99 | 0.24 |
| puddle | -1.85 | -2.05 | 0.20 |
| potato | -3.45 | -3.60 | 0.15 |
| saddle | -1.27 | -1.39 | 0.11 |
| foam | -1.07 | -1.17 | 0.09 |
| fruitcake | -2.30 | -2.38 | 0.07 |
| shirt | -3.02 | -3.06 | 0.04 |
| mandolin | -0.60 | -0.64 | 0.04 |
| footbath | -3.30 | -3.34 | 0.04 |
| tongue | -3.89 | -3.90 | 0.02 |
| locker | -3.13 | -3.10 | -0.03 |
| bamboo | -2.75 | -2.69 | -0.05 |
| flan | 1.28 | 1.34 | -0.06 |
| fan | -3.28 | -3.19 | -0.09 |
| modem | -0.73 | -0.60 | -0.13 |
| barrel | -2.48 | -2.32 | -0.16 |
| sorbet | -0.94 | -0.74 | -0.20 |
| stretcher | -2.12 | -1.86 | -0.25 |
| coffee | -2.92 | -2.61 | -0.30 |
| carrot | -3.20 | -2.83 | -0.37 |
| map | -3.05 | -2.68 | -0.38 |
| cake | -3.61 | -3.14 | -0.47 |
| strap | -2.38 | -1.83 | -0.55 |
| syringe | -0.97 | -0.35 | -0.62 |
| sloth | -2.24 | -1.61 | -0.63 |
| fence | -3.34 | -2.70 | -0.64 |
| kimono | -0.87 | -0.21 | -0.66 |
| pitcher | 1.49 | 2.16 | -0.67 |
| lollipop | -3.82 | -3.13 | -0.69 |
| hedgehog | -3.13 | -2.24 | -0.88 |
| honey | -3.36 | -2.28 | -1.08 |
| scrabble | 0.14 | 1.30 | -1.16 |
| pistachio | -2.03 | -0.76 | -1.27 |
| chandelier | -3.71 | -2.32 | -1.39 |
| aloe | -1.12 | 1.50 | -2.62 |
| coaster | -1.18 | 1.87 | -3.05 |
| mulch | NA | 1.23 | NA |
| cymbal | NA | 0.44 | NA |
| kayak | NA | -0.78 | NA |
| omelet | NA | -0.95 | NA |
| blower | -1.13 | NA | NA |
| biscuit | NA | -1.79 | NA |
| fox | -1.82 | NA | NA |
| taillight | NA | -1.97 | NA |
| screw | -2.04 | NA | NA |
| koala | -2.05 | NA | NA |
| squash | NA | -2.29 | NA |
| papaya | NA | -2.31 | NA |
| gazelle | NA | -2.32 | NA |
| otter | NA | -2.47 | NA |
| candlestick | NA | -2.55 | NA |
| horn | NA | -2.72 | NA |
| spatula | NA | -2.86 | NA |
| milkshake | NA | -3.26 | NA |
| sprinkler | NA | -3.63 | NA |
| marshmallow | NA | -3.89 | NA |
| pie | NA | -3.92 | NA |
| elbow | NA | -4.37 | NA |
Thetas with these two different models
thetas_by_all_subs <- thetas_by_all_subs %>%
right_join(all_thetas_with_matched_subset)ggplot(data = thetas_by_all_subs, aes(x=theta_2pl_all_data, y=theta_2pl_matched_data, col=age)) +
geom_point(alpha=.8) +
geom_smooth(method='lm', color='grey',alpha=.2) +
theme_few() +
ylab('Theta estimates') +
xlab('Theta estimates') +
scale_color_viridis_c() +
facet_wrap(~age, nrow=2) +
theme(legend.position='right') +
theme(aspect.ratio=.75)