Desperation Study 2 Preliminary Results
1 Demographics
1.1 Gender
1.2 Sexual Orientation
1.3 English as a first language
1.4 Relationship Status
1.5 Race
2 Descriptives
2.1 General
2.2 Correlations
3 EFA (First 350 participants)
3.1 Skree, parallel, and Bartlett
## Parallel analysis suggests that the number of factors = 6 and the number of components = NA3.2 Individual Item MSAs
3.3 Factor Loadings
3.4 Eigenvalues
3.5 Trying Six factors
Since parallel analysis suggested 6, I thought I would just give it a try.
3.6 Additional Diagnostics
4 Five-Factor EFA: Full-Sample
4.1 Skree, parallel, and Bartlett - Full-Sample
## Parallel analysis suggests that the number of factors = 7 and the number of components = NA4.2 EFA Diagnostics — Full Sample
4.3 Item-Level KMO — Full Sample
4.4 Factor Loadings - Full Sample
4.5 Item-Level Diagnostics — Full Sample
4.6 Eigenvalues — Full Sample
5 Five-Factor EFA - English as a First Language Only
5.1 Skree, parallel, and Bartlett
## Parallel analysis suggests that the number of factors = 5 and the number of components = NA5.2 EFA Diagnostics — English Sample
5.3 Item-Level KMO — English Sample
5.4 Factor Loadings - English Sample
5.5 Item-Level Diagnostics — English Sample
5.6 Eigenvalues — English Sample
6 Five-Factor EFA - Language Exclusion & Reverse Coded Items Removed
6.1 Skree, parallel, and Bartlett
## Parallel analysis suggests that the number of factors = 4 and the number of components = NA6.2 EFA Diagnostics
6.3 Item-Level KMO
6.4 Factor Loadings
6.5 Item-Level Diagnostics
6.6 Eigenvalues
7 Five-Factor EFA - Removing Double Loadings Etc.
7.1 Skree, parallel, and Bartlett
## Parallel analysis suggests that the number of factors = 4 and the number of components = NA7.2 Factor Loadings
8 Four-Factor EFA - Final v2
8.1 Skree, parallel, and Bartlett
## Parallel analysis suggests that the number of factors = 4 and the number of components = NA8.2 Factor Loadings
8.3 Eigenvalues
9 Confirmatory Factor Analysis (English as a first language)
## Total English-first-language participants: 646## EFA participants: 350## CFA participants before missing-data exclusions: 296## CFA participants with complete 12-item data: 292## CFA participants excluded for missing data: 49.1 Fitting the CFA
9.1.1 Did the model converge?
## [1] TRUE9.1.2 CFA Full output
## lavaan 0.7-3 ended normally after 30 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of model parameters 114
##
## Number of observations 292
##
## Model Test User Model:
## Standard Scaled
## Test Statistic 206.005 294.400
## Degrees of freedom 48 48
## P-value (Unknown) NA 0.000
## Scaling correction factor 0.737
## Shift parameter 14.745
## simple second-order correction
##
## Model Test Baseline Model:
##
## Test statistic 8445.492 3952.570
## Degrees of freedom 66 66
## P-value NA 0.000
## Scaling correction factor 2.156
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.981 0.937
## Tucker-Lewis Index (TLI) 0.974 0.913
##
## Robust Comparative Fit Index (CFI) 0.923
## Robust Tucker-Lewis Index (TLI) 0.894
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.106 0.133
## 90 Percent confidence interval - lower 0.092 0.118
## 90 Percent confidence interval - upper 0.122 0.148
## P-value H_0: RMSEA <= 0.050 0.000 0.000
## P-value H_0: RMSEA >= 0.080 0.998 1.000
##
## Robust RMSEA 0.095
## 90 Percent confidence interval - lower 0.080
## 90 Percent confidence interval - upper 0.110
## P-value H_0: Robust RMSEA <= 0.050 0.000
## P-value H_0: Robust RMSEA >= 0.080 0.952
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.078 0.078
##
## Goodness of Fit Index:
##
## Goodness of Fit Index (GFI) 0.917
## 90 Percent confidence interval - lower 0.894
## 90 Percent confidence interval - upper 0.937
##
## Robust GFI 0.933
## 90 Percent confidence interval - lower 0.912
## 90 Percent confidence interval - upper 0.951
##
## Parameter Estimates:
##
## Parameterization Delta
## Standard errors Robust.sem
## Information Expected
## Information bread Observed
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Desire =~
## DesprtSlf_Ds14 0.853 0.019 44.999 0.000 0.853 0.853
## DesprtSlf_Ds10 0.879 0.017 50.420 0.000 0.879 0.879
## DesprtSlf_Ds11 0.924 0.014 64.839 0.000 0.924 0.924
## Energy =~
## DesprtSlf_Gl34 0.789 0.030 26.195 0.000 0.789 0.789
## DsprtSlf_Ovr18 0.858 0.022 39.162 0.000 0.858 0.858
## DsprtSlf_Ovr17 0.729 0.033 21.978 0.000 0.729 0.729
## Comparison =~
## DesprtSlf_Ln32 0.462 0.050 9.296 0.000 0.462 0.462
## DesprtSlf_Unc1 0.961 0.061 15.822 0.000 0.961 0.961
## DesprtSlf_Ln29 0.538 0.051 10.543 0.000 0.538 0.538
## Overinvestment =~
## DsprtSlf_Ovr24 0.462 0.044 10.394 0.000 0.462 0.462
## DsprtSlf_Ovr23 0.602 0.040 14.891 0.000 0.602 0.602
## DesprtSlf_Unc8 0.580 0.045 12.873 0.000 0.580 0.580
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Desire ~~
## Energy 0.480 0.047 10.268 0.000 0.480 0.480
## Comparison 0.508 0.046 10.997 0.000 0.508 0.508
## Overinvestment 0.790 0.048 16.328 0.000 0.790 0.790
## Energy ~~
## Comparison 0.122 0.062 1.973 0.048 0.122 0.122
## Overinvestment 0.809 0.045 18.026 0.000 0.809 0.809
## Comparison ~~
## Overinvestment 0.622 0.051 12.265 0.000 0.622 0.622
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DsprtSlf_D14|1 -2.465 0.254 -9.713 0.000 -2.465 -2.465
## DsprtSlf_D14|2 -2.117 0.180 -11.769 0.000 -2.117 -2.117
## DsprtSlf_D14|3 -1.700 0.129 -13.172 0.000 -1.700 -1.700
## DsprtSlf_D14|4 -1.413 0.108 -13.106 0.000 -1.413 -1.413
## DsprtSlf_D14|5 -0.923 0.086 -10.686 0.000 -0.923 -0.923
## DsprtSlf_D14|6 -0.360 0.075 -4.764 0.000 -0.360 -0.360
## DsprtSlf_D14|7 0.129 0.074 1.746 0.081 0.129 0.129
## DsprtSlf_D14|8 0.718 0.081 8.860 0.000 0.718 0.718
## DsprtSlf_D10|1 -1.978 0.159 -12.403 0.000 -1.978 -1.978
## DsprtSlf_D10|2 -1.665 0.126 -13.214 0.000 -1.665 -1.665
## DsprtSlf_D10|3 -1.413 0.108 -13.106 0.000 -1.413 -1.413
## DsprtSlf_D10|4 -1.110 0.093 -11.953 0.000 -1.110 -1.110
## DsprtSlf_D10|5 -0.707 0.081 -8.749 0.000 -0.707 -0.707
## DsprtSlf_D10|6 -0.112 0.074 -1.513 0.130 -0.112 -0.112
## DsprtSlf_D10|7 0.360 0.075 4.764 0.000 0.360 0.360
## DsprtSlf_D10|8 0.763 0.082 9.300 0.000 0.763 0.763
## DsprtSlf_D11|1 -1.978 0.159 -12.403 0.000 -1.978 -1.978
## DsprtSlf_D11|2 -1.665 0.126 -13.214 0.000 -1.665 -1.665
## DsprtSlf_D11|3 -1.266 0.100 -12.689 0.000 -1.266 -1.266
## DsprtSlf_D11|4 -0.923 0.086 -10.686 0.000 -0.923 -0.923
## DsprtSlf_D11|5 -0.462 0.077 -6.031 0.000 -0.462 -0.462
## DsprtSlf_D11|6 0.077 0.074 1.048 0.295 0.077 0.077
## DsprtSlf_D11|7 0.540 0.078 6.947 0.000 0.540 0.540
## DsprtSlf_D11|8 0.910 0.086 10.583 0.000 0.910 0.910
## DsprtSlf_G34|1 -1.126 0.093 -12.042 0.000 -1.126 -1.126
## DsprtSlf_G34|2 -0.540 0.078 -6.947 0.000 -0.540 -0.540
## DsprtSlf_G34|3 0.120 0.074 1.630 0.103 0.120 0.120
## DsprtSlf_G34|4 0.560 0.078 7.174 0.000 0.560 0.560
## DsprtSlf_G34|5 0.936 0.087 10.789 0.000 0.936 0.936
## DsprtSlf_G34|6 1.413 0.108 13.106 0.000 1.413 1.413
## DsprtSlf_G34|7 1.822 0.141 12.926 0.000 1.822 1.822
## DsprtSlf_G34|8 1.921 0.152 12.620 0.000 1.921 1.921
## DsprtSlf_O18|1 -1.159 0.095 -12.215 0.000 -1.159 -1.159
## DsprtSlf_O18|2 -0.520 0.077 -6.718 0.000 -0.520 -0.520
## DsprtSlf_O18|3 0.120 0.074 1.630 0.103 0.120 0.120
## DsprtSlf_O18|4 0.520 0.077 6.718 0.000 0.520 0.520
## DsprtSlf_O18|5 0.949 0.087 10.891 0.000 0.949 0.949
## DsprtSlf_O18|6 1.487 0.113 13.215 0.000 1.487 1.487
## DsprtSlf_O18|7 1.822 0.141 12.926 0.000 1.822 1.822
## DsprtSlf_O18|8 2.206 0.195 11.299 0.000 2.206 2.206
## DsprtSlf_O17|1 -1.326 0.103 -12.890 0.000 -1.326 -1.326
## DsprtSlf_O17|2 -0.787 0.083 -9.518 0.000 -0.787 -0.787
## DsprtSlf_O17|3 -0.332 0.075 -4.417 0.000 -0.332 -0.332
## DsprtSlf_O17|4 0.043 0.074 0.582 0.560 0.043 0.043
## DsprtSlf_O17|5 0.491 0.077 6.375 0.000 0.491 0.491
## DsprtSlf_O17|6 0.871 0.085 10.269 0.000 0.871 0.871
## DsprtSlf_O17|7 1.665 0.126 13.214 0.000 1.665 1.665
## DsprtSlf_O17|8 2.117 0.180 11.769 0.000 2.117 2.117
## DsprtSlf_L32|1 -1.921 0.152 -12.620 0.000 -1.921 -1.921
## DsprtSlf_L32|2 -1.541 0.116 -13.254 0.000 -1.541 -1.541
## DsprtSlf_L32|3 -1.110 0.093 -11.953 0.000 -1.110 -1.110
## DsprtSlf_L32|4 -0.718 0.081 -8.860 0.000 -0.718 -0.718
## DsprtSlf_L32|5 -0.129 0.074 -1.746 0.081 -0.129 -0.129
## DsprtSlf_L32|6 0.269 0.075 3.605 0.000 0.269 0.269
## DsprtSlf_L32|7 0.834 0.084 9.950 0.000 0.834 0.834
## DsprtSlf_L32|8 1.176 0.096 12.300 0.000 1.176 1.176
## DsprtSlf_Un1|1 -1.921 0.152 -12.620 0.000 -1.921 -1.921
## DsprtSlf_Un1|2 -1.632 0.123 -13.242 0.000 -1.632 -1.632
## DsprtSlf_Un1|3 -1.126 0.093 -12.042 0.000 -1.126 -1.126
## DsprtSlf_Un1|4 -0.810 0.083 -9.735 0.000 -0.810 -0.810
## DsprtSlf_Un1|5 -0.387 0.076 -5.110 0.000 -0.387 -0.387
## DsprtSlf_Un1|6 0.146 0.074 1.979 0.048 0.146 0.146
## DsprtSlf_Un1|7 0.643 0.080 8.079 0.000 0.643 0.643
## DsprtSlf_Un1|8 1.126 0.093 12.042 0.000 1.126 1.126
## DsprtSlf_L29|1 -1.176 0.096 -12.300 0.000 -1.176 -1.176
## DsprtSlf_L29|2 -0.810 0.083 -9.735 0.000 -0.810 -0.810
## DsprtSlf_L29|3 -0.287 0.075 -3.837 0.000 -0.287 -0.287
## DsprtSlf_L29|4 0.069 0.074 0.931 0.352 0.069 0.069
## DsprtSlf_L29|5 0.482 0.077 6.261 0.000 0.482 0.482
## DsprtSlf_L29|6 0.822 0.084 9.843 0.000 0.822 0.822
## DsprtSlf_L29|7 1.305 0.102 12.826 0.000 1.305 1.305
## DsprtSlf_L29|8 1.778 0.136 13.031 0.000 1.778 1.778
## DsprtSlf_O24|1 -1.541 0.116 -13.254 0.000 -1.541 -1.541
## DsprtSlf_O24|2 -1.063 0.091 -11.676 0.000 -1.063 -1.063
## DsprtSlf_O24|3 -0.501 0.077 -6.490 0.000 -0.501 -0.501
## DsprtSlf_O24|4 -0.060 0.074 -0.815 0.415 -0.060 -0.060
## DsprtSlf_O24|5 0.406 0.076 5.341 0.000 0.406 0.406
## DsprtSlf_O24|6 0.798 0.083 9.627 0.000 0.798 0.798
## DsprtSlf_O24|7 1.211 0.097 12.462 0.000 1.211 1.211
## DsprtSlf_O24|8 1.665 0.126 13.214 0.000 1.665 1.665
## DsprtSlf_O23|1 -1.305 0.102 -12.826 0.000 -1.305 -1.305
## DsprtSlf_O23|2 -0.949 0.087 -10.891 0.000 -0.949 -0.949
## DsprtSlf_O23|3 -0.482 0.077 -6.261 0.000 -0.482 -0.482
## DsprtSlf_O23|4 -0.086 0.074 -1.164 0.244 -0.086 -0.086
## DsprtSlf_O23|5 0.601 0.079 7.628 0.000 0.601 0.601
## DsprtSlf_O23|6 0.977 0.088 11.093 0.000 0.977 0.977
## DsprtSlf_O23|7 1.600 0.121 13.257 0.000 1.600 1.600
## DsprtSlf_O23|8 1.778 0.136 13.031 0.000 1.778 1.778
## DsprtSlf_Un8|1 -1.738 0.133 -13.111 0.000 -1.738 -1.738
## DsprtSlf_Un8|2 -1.487 0.113 -13.215 0.000 -1.487 -1.487
## DsprtSlf_Un8|3 -1.176 0.096 -12.300 0.000 -1.176 -1.176
## DsprtSlf_Un8|4 -0.834 0.084 -9.950 0.000 -0.834 -0.834
## DsprtSlf_Un8|5 -0.482 0.077 -6.261 0.000 -0.482 -0.482
## DsprtSlf_Un8|6 0.069 0.074 0.931 0.352 0.069 0.069
## DsprtSlf_Un8|7 0.664 0.080 8.303 0.000 0.664 0.664
## DsprtSlf_Un8|8 1.005 0.089 11.291 0.000 1.005 1.005
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DesprtSlf_Ds14 0.273 0.273 0.273
## .DesprtSlf_Ds10 0.227 0.227 0.227
## .DesprtSlf_Ds11 0.146 0.146 0.146
## .DesprtSlf_Gl34 0.377 0.377 0.377
## .DsprtSlf_Ovr18 0.264 0.264 0.264
## .DsprtSlf_Ovr17 0.468 0.468 0.468
## .DesprtSlf_Ln32 0.787 0.787 0.787
## .DesprtSlf_Unc1 0.076 0.076 0.076
## .DesprtSlf_Ln29 0.711 0.711 0.711
## .DsprtSlf_Ovr24 0.786 0.786 0.786
## .DsprtSlf_Ovr23 0.637 0.637 0.637
## .DesprtSlf_Unc8 0.663 0.663 0.663
## Desire 1.000 1.000 1.000
## Energy 1.000 1.000 1.000
## Comparison 1.000 1.000 1.000
## Overinvestment 1.000 1.000 1.000
##
## R-Square:
## Estimate
## DesprtSlf_Ds14 0.727
## DesprtSlf_Ds10 0.773
## DesprtSlf_Ds11 0.854
## DesprtSlf_Gl34 0.623
## DsprtSlf_Ovr18 0.736
## DsprtSlf_Ovr17 0.532
## DesprtSlf_Ln32 0.213
## DesprtSlf_Unc1 0.924
## DesprtSlf_Ln29 0.289
## DsprtSlf_Ovr24 0.214
## DsprtSlf_Ovr23 0.363
## DesprtSlf_Unc8 0.3379.1.3 Fit Statistics
## chisq.scaled df.scaled pvalue.scaled cfi.robust tli.robust
## 294.40047383 48.00000000 0.00000000 0.92277656 0.89381777
## rmsea.robust srmr
## 0.09476496 0.077577619.2 Factor loadings
9.3 Factor correlations
9.4 Item-level explained variance
9.5 Potential Estimation Problems
10 CFA For all first languages
## Total participants: 781## Original EFA N: 350## Second CFA candidates: 431## Second CFA complete-case N: 413## Excluded for missing data: 18## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative10.0.1 Examining potential problems with comparison items
10.1 Fitting the model
10.1.1 Does it Converge?
## [1] TRUE10.1.2 CFA full output
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative## lavaan 0.7-3 ended normally after 32 iterations
##
## Estimator DWLS
## Optimization method NLMINB
## Number of model parameters 114
##
## Number of observations 413
##
## Model Test User Model:
## Standard Scaled
## Test Statistic 298.685 425.555
## Degrees of freedom 48 48
## P-value (Unknown) NA 0.000
## Scaling correction factor 0.725
## Shift parameter 13.537
## simple second-order correction
##
## Model Test Baseline Model:
##
## Test statistic 9520.203 4667.448
## Degrees of freedom 66 66
## P-value NA 0.000
## Scaling correction factor 2.055
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.973 0.918
## Tucker-Lewis Index (TLI) 0.964 0.887
##
## Robust Comparative Fit Index (CFI) 0.897
## Robust Tucker-Lewis Index (TLI) 0.859
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.113 0.138
## 90 Percent confidence interval - lower 0.101 0.126
## 90 Percent confidence interval - upper 0.125 0.150
## P-value H_0: RMSEA <= 0.050 0.000 0.000
## P-value H_0: RMSEA >= 0.080 1.000 1.000
##
## Robust RMSEA 0.104
## 90 Percent confidence interval - lower 0.092
## 90 Percent confidence interval - upper 0.116
## P-value H_0: Robust RMSEA <= 0.050 0.000
## P-value H_0: Robust RMSEA >= 0.080 1.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.078 0.078
##
## Goodness of Fit Index:
##
## Goodness of Fit Index (GFI) 0.908
## 90 Percent confidence interval - lower 0.889
## 90 Percent confidence interval - upper 0.925
##
## Robust GFI 0.920
## 90 Percent confidence interval - lower 0.903
## 90 Percent confidence interval - upper 0.936
##
## Parameter Estimates:
##
## Parameterization Delta
## Standard errors Robust.sem
## Information Expected
## Information bread Observed
## Information saturated (h1) model Unstructured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Desire =~
## DesprtSlf_Ds14 0.830 0.018 46.892 0.000 0.830 0.830
## DesprtSlf_Ds10 0.884 0.016 54.311 0.000 0.884 0.884
## DesprtSlf_Ds11 0.889 0.016 54.864 0.000 0.889 0.889
## Energy =~
## DesprtSlf_Gl34 0.762 0.027 27.807 0.000 0.762 0.762
## DsprtSlf_Ovr18 0.797 0.025 31.752 0.000 0.797 0.797
## DsprtSlf_Ovr17 0.720 0.030 24.249 0.000 0.720 0.720
## Comparison =~
## DesprtSlf_Ln32 0.409 0.046 8.959 0.000 0.409 0.409
## DesprtSlf_Unc1 1.011 0.063 16.063 0.000 1.011 1.011
## DesprtSlf_Ln29 0.493 0.048 10.264 0.000 0.493 0.493
## Overinvestment =~
## DsprtSlf_Ovr24 0.447 0.038 11.699 0.000 0.447 0.447
## DsprtSlf_Ovr23 0.610 0.033 18.198 0.000 0.610 0.610
## DesprtSlf_Unc8 0.605 0.038 16.036 0.000 0.605 0.605
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## Desire ~~
## Energy 0.436 0.043 10.224 0.000 0.436 0.436
## Comparison 0.462 0.040 11.436 0.000 0.462 0.462
## Overinvestment 0.767 0.039 19.726 0.000 0.767 0.767
## Energy ~~
## Comparison 0.161 0.054 2.972 0.003 0.161 0.161
## Overinvestment 0.849 0.036 23.429 0.000 0.849 0.849
## Comparison ~~
## Overinvestment 0.572 0.049 11.719 0.000 0.572 0.572
##
## Thresholds:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## DsprtSlf_D14|1 -2.254 0.172 -13.134 0.000 -2.254 -2.254
## DsprtSlf_D14|2 -2.067 0.144 -14.309 0.000 -2.067 -2.067
## DsprtSlf_D14|3 -1.660 0.105 -15.745 0.000 -1.660 -1.660
## DsprtSlf_D14|4 -1.390 0.089 -15.552 0.000 -1.390 -1.390
## DsprtSlf_D14|5 -0.900 0.072 -12.514 0.000 -0.900 -0.900
## DsprtSlf_D14|6 -0.350 0.063 -5.529 0.000 -0.350 -0.350
## DsprtSlf_D14|7 0.192 0.062 3.087 0.002 0.192 0.192
## DsprtSlf_D14|8 0.739 0.068 10.794 0.000 0.739 0.739
## DsprtSlf_D10|1 -1.933 0.129 -14.979 0.000 -1.933 -1.933
## DsprtSlf_D10|2 -1.592 0.101 -15.792 0.000 -1.592 -1.592
## DsprtSlf_D10|3 -1.343 0.087 -15.414 0.000 -1.343 -1.343
## DsprtSlf_D10|4 -1.005 0.075 -13.454 0.000 -1.005 -1.005
## DsprtSlf_D10|5 -0.602 0.066 -9.100 0.000 -0.602 -0.602
## DsprtSlf_D10|6 -0.058 0.062 -0.931 0.352 -0.058 -0.058
## DsprtSlf_D10|7 0.395 0.064 6.210 0.000 0.395 0.395
## DsprtSlf_D10|8 0.821 0.070 11.711 0.000 0.821 0.821
## DsprtSlf_D11|1 -1.933 0.129 -14.979 0.000 -1.933 -1.933
## DsprtSlf_D11|2 -1.660 0.105 -15.745 0.000 -1.660 -1.660
## DsprtSlf_D11|3 -1.232 0.082 -14.953 0.000 -1.232 -1.232
## DsprtSlf_D11|4 -0.864 0.071 -12.160 0.000 -0.864 -0.864
## DsprtSlf_D11|5 -0.415 0.064 -6.501 0.000 -0.415 -0.415
## DsprtSlf_D11|6 0.106 0.062 1.716 0.086 0.106 0.106
## DsprtSlf_D11|7 0.609 0.066 9.195 0.000 0.609 0.609
## DsprtSlf_D11|8 1.026 0.075 13.618 0.000 1.026 1.026
## DsprtSlf_G34|1 -1.015 0.075 -13.536 0.000 -1.015 -1.015
## DsprtSlf_G34|2 -0.489 0.065 -7.565 0.000 -0.489 -0.489
## DsprtSlf_G34|3 0.106 0.062 1.716 0.086 0.106 0.106
## DsprtSlf_G34|4 0.573 0.066 8.718 0.000 0.573 0.573
## DsprtSlf_G34|5 0.937 0.073 12.862 0.000 0.937 0.937
## DsprtSlf_G34|6 1.492 0.095 15.747 0.000 1.492 1.492
## DsprtSlf_G34|7 1.895 0.125 15.136 0.000 1.895 1.895
## DsprtSlf_G34|8 2.067 0.144 14.309 0.000 2.067 2.067
## DsprtSlf_O18|1 -1.170 0.080 -14.615 0.000 -1.170 -1.170
## DsprtSlf_O18|2 -0.538 0.065 -8.239 0.000 -0.538 -0.538
## DsprtSlf_O18|3 0.064 0.062 1.030 0.303 0.064 0.064
## DsprtSlf_O18|4 0.455 0.064 7.082 0.000 0.455 0.455
## DsprtSlf_O18|5 0.937 0.073 12.862 0.000 0.937 0.937
## DsprtSlf_O18|6 1.422 0.091 15.630 0.000 1.422 1.422
## DsprtSlf_O18|7 1.826 0.119 15.381 0.000 1.826 1.826
## DsprtSlf_O18|8 2.121 0.152 13.993 0.000 2.121 2.121
## DsprtSlf_O17|1 -1.272 0.084 -15.139 0.000 -1.272 -1.272
## DsprtSlf_O17|2 -0.804 0.070 -11.529 0.000 -0.804 -0.804
## DsprtSlf_O17|3 -0.356 0.063 -5.626 0.000 -0.356 -0.356
## DsprtSlf_O17|4 0.003 0.062 0.049 0.961 0.003 0.003
## DsprtSlf_O17|5 0.476 0.065 7.372 0.000 0.476 0.476
## DsprtSlf_O17|6 0.873 0.071 12.249 0.000 0.873 0.873
## DsprtSlf_O17|7 1.592 0.101 15.792 0.000 1.592 1.592
## DsprtSlf_O17|8 2.067 0.144 14.309 0.000 2.067 2.067
## DsprtSlf_L32|1 -1.795 0.116 -15.475 0.000 -1.795 -1.795
## DsprtSlf_L32|2 -1.456 0.093 -15.696 0.000 -1.456 -1.456
## DsprtSlf_L32|3 -1.112 0.078 -14.249 0.000 -1.112 -1.112
## DsprtSlf_L32|4 -0.684 0.067 -10.140 0.000 -0.684 -0.684
## DsprtSlf_L32|5 -0.094 0.062 -1.520 0.129 -0.094 -0.094
## DsprtSlf_L32|6 0.292 0.063 4.651 0.000 0.292 0.292
## DsprtSlf_L32|7 0.830 0.070 11.801 0.000 0.830 0.830
## DsprtSlf_L32|8 1.219 0.082 14.888 0.000 1.219 1.219
## DsprtSlf_Un1|1 -1.711 0.109 -15.671 0.000 -1.711 -1.711
## DsprtSlf_Un1|2 -1.422 0.091 -15.630 0.000 -1.422 -1.422
## DsprtSlf_Un1|3 -1.015 0.075 -13.536 0.000 -1.015 -1.015
## DsprtSlf_Un1|4 -0.676 0.067 -10.046 0.000 -0.676 -0.676
## DsprtSlf_Un1|5 -0.248 0.063 -3.967 0.000 -0.248 -0.248
## DsprtSlf_Un1|6 0.242 0.063 3.870 0.000 0.242 0.242
## DsprtSlf_Un1|7 0.699 0.068 10.328 0.000 0.699 0.699
## DsprtSlf_Un1|8 1.170 0.080 14.615 0.000 1.170 1.170
## DsprtSlf_L29|1 -1.112 0.078 -14.249 0.000 -1.112 -1.112
## DsprtSlf_L29|2 -0.755 0.069 -10.979 0.000 -0.755 -0.755
## DsprtSlf_L29|3 -0.286 0.063 -4.554 0.000 -0.286 -0.286
## DsprtSlf_L29|4 0.070 0.062 1.128 0.260 0.070 0.070
## DsprtSlf_L29|5 0.489 0.065 7.565 0.000 0.489 0.489
## DsprtSlf_L29|6 0.838 0.070 11.892 0.000 0.838 0.838
## DsprtSlf_L29|7 1.300 0.085 15.255 0.000 1.300 1.300
## DsprtSlf_L29|8 1.826 0.119 15.381 0.000 1.826 1.826
## DsprtSlf_O24|1 -1.406 0.090 -15.592 0.000 -1.406 -1.406
## DsprtSlf_O24|2 -0.995 0.074 -13.371 0.000 -0.995 -0.995
## DsprtSlf_O24|3 -0.538 0.065 -8.239 0.000 -0.538 -0.538
## DsprtSlf_O24|4 -0.125 0.062 -2.010 0.044 -0.125 -0.125
## DsprtSlf_O24|5 0.331 0.063 5.236 0.000 0.331 0.331
## DsprtSlf_O24|6 0.723 0.068 10.608 0.000 0.723 0.723
## DsprtSlf_O24|7 1.207 0.081 14.822 0.000 1.207 1.207
## DsprtSlf_O24|8 1.711 0.109 15.671 0.000 1.711 1.711
## DsprtSlf_O23|1 -1.182 0.080 -14.685 0.000 -1.182 -1.182
## DsprtSlf_O23|2 -0.873 0.071 -12.249 0.000 -0.873 -0.873
## DsprtSlf_O23|3 -0.489 0.065 -7.565 0.000 -0.489 -0.489
## DsprtSlf_O23|4 -0.119 0.062 -1.912 0.056 -0.119 -0.119
## DsprtSlf_O23|5 0.510 0.065 7.854 0.000 0.510 0.510
## DsprtSlf_O23|6 0.928 0.073 12.776 0.000 0.928 0.928
## DsprtSlf_O23|7 1.550 0.098 15.790 0.000 1.550 1.550
## DsprtSlf_O23|8 1.933 0.129 14.979 0.000 1.933 1.933
## DsprtSlf_Un8|1 -1.711 0.109 -15.671 0.000 -1.711 -1.711
## DsprtSlf_Un8|2 -1.492 0.095 -15.747 0.000 -1.492 -1.492
## DsprtSlf_Un8|3 -1.170 0.080 -14.615 0.000 -1.170 -1.170
## DsprtSlf_Un8|4 -0.838 0.070 -11.892 0.000 -0.838 -0.838
## DsprtSlf_Un8|5 -0.469 0.064 -7.276 0.000 -0.469 -0.469
## DsprtSlf_Un8|6 0.070 0.062 1.128 0.260 0.070 0.070
## DsprtSlf_Un8|7 0.609 0.066 9.195 0.000 0.609 0.609
## DsprtSlf_Un8|8 1.015 0.075 13.536 0.000 1.015 1.015
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .DesprtSlf_Ds14 0.312 0.312 0.312
## .DesprtSlf_Ds10 0.218 0.218 0.218
## .DesprtSlf_Ds11 0.209 0.209 0.209
## .DesprtSlf_Gl34 0.420 0.420 0.420
## .DsprtSlf_Ovr18 0.365 0.365 0.365
## .DsprtSlf_Ovr17 0.481 0.481 0.481
## .DesprtSlf_Ln32 0.833 0.833 0.833
## .DesprtSlf_Unc1 -0.021 -0.021 -0.021
## .DesprtSlf_Ln29 0.756 0.756 0.756
## .DsprtSlf_Ovr24 0.800 0.800 0.800
## .DsprtSlf_Ovr23 0.628 0.628 0.628
## .DesprtSlf_Unc8 0.634 0.634 0.634
## Desire 1.000 1.000 1.000
## Energy 1.000 1.000 1.000
## Comparison 1.000 1.000 1.000
## Overinvestment 1.000 1.000 1.000
##
## R-Square:
## Estimate
## DesprtSlf_Ds14 0.688
## DesprtSlf_Ds10 0.782
## DesprtSlf_Ds11 0.791
## DesprtSlf_Gl34 0.580
## DsprtSlf_Ovr18 0.635
## DsprtSlf_Ovr17 0.519
## DesprtSlf_Ln32 0.167
## DesprtSlf_Unc1 NA
## DesprtSlf_Ln29 0.244
## DsprtSlf_Ovr24 0.200
## DsprtSlf_Ovr23 0.372
## DesprtSlf_Unc8 0.36610.1.3 Fit statistics
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative## chisq.scaled df.scaled pvalue.scaled cfi.robust tli.robust
## 425.55504017 48.00000000 0.00000000 0.89747984 0.85903478
## rmsea.robust srmr
## 0.10393266 0.0781881710.2 Standardized Factor Loadings
10.3 Factor Correlations
pvalue.scaled cfi.robust tli.robust rmsea.robust srmr 425.55504017 48.00000000 0.00000000 0.8## Item-level explained variance
10.4 Residual variances and standardized estimates
10.5 Compare the two CFA models
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative
## Warning: lavaan->lav_object_post_check():
## some estimated ov variances are negative10.6 Convergent & Discriminant Validity
10.6.1 Correlation Matrix
11 Study 3 (Maybe) from HDDM Data
11.1 Yes/No in top 25% vs. Bottom 25%
11.2 Correlations
11.3 Regression
11.3.1 Yes/No = Overall Desperation
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: response ~ Desperation_Overall * normAttractive + (1 | subj_idx)
## Data: attractiveness_data
##
## AIC BIC logLik -2*log(L) df.resid
## 9144.5 9184.8 -4567.2 9134.5 23595
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.2096 -0.2448 -0.1239 -0.0628 13.9777
##
## Random effects:
## Groups Name Variance Std.Dev.
## subj_idx (Intercept) 3.045 1.745
## Number of obs: 23600, groups: subj_idx, 118
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -9.562155 1.180563 -8.100 5.51e-16 ***
## Desperation_Overall 0.367981 0.218452 1.684 0.0921 .
## normAttractive 1.199472 0.205828 5.828 5.62e-09 ***
## Desperation_Overall:normAttractive -0.004727 0.038113 -0.124 0.9013
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Dspr_O nrmAtt
## Dsprtn_Ovrl -0.981
## normAttrctv -0.648 0.635
## Dsprtn_Ov:A 0.634 -0.647 -0.980## (Intercept) Desperation_Overall
## 7.034106e-05 1.444815e+00
## normAttractive Desperation_Overall:normAttractive
## 3.318365e+00 9.952839e-01## 2.5 % 97.5 %
## (Intercept) 6.955232e-06 0.0007113874
## Desperation_Overall 9.415976e-01 2.2169666891
## normAttractive 2.216785e+00 4.9673516992
## Desperation_Overall:normAttractive 9.236452e-01 1.072478960811.3.2 Response Time = Overall Desperation
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: rt ~ Desperation_Overall * normAttractive + (1 | subj_idx)
## Data: attractiveness_data
##
## REML criterion at convergence: 72966.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.463 -0.321 -0.119 0.091 44.126
##
## Random effects:
## Groups Name Variance Std.Dev.
## subj_idx (Intercept) 0.4412 0.6642
## Residual 1.2609 1.1229
## Number of obs: 23600, groups: subj_idx, 118
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) 4.767e-01 3.681e-01 1.925e+02 1.295
## Desperation_Overall 3.910e-02 6.857e-02 1.923e+02 0.570
## normAttractive 4.197e-02 5.325e-02 2.353e+04 0.788
## Desperation_Overall:normAttractive 1.626e-02 9.897e-03 2.353e+04 1.643
## Pr(>|t|)
## (Intercept) 0.197
## Desperation_Overall 0.569
## normAttractive 0.431
## Desperation_Overall:normAttractive 0.100
##
## Correlation of Fixed Effects:
## (Intr) Dspr_O nrmAtt
## Dsprtn_Ovrl -0.982
## normAttrctv -0.473 0.464
## Dsprtn_Ov:A 0.465 -0.473 -0.98211.3.3 Yes/No = Desperation Subconstructs
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula:
## response ~ Desperation_Desire + Desperation_Energy + Desperation_Comparison +
## Desperation_Overinvestment + (1 | subj_idx)
## Data: regression_data
##
## AIC BIC logLik -2*log(L) df.resid
## 10098.8 10147.2 -5043.4 10086.8 23594
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.7409 -0.2924 -0.1447 -0.0832 12.4671
##
## Random effects:
## Groups Name Variance Std.Dev.
## subj_idx (Intercept) 2.816 1.678
## Number of obs: 23600, groups: subj_idx, 118
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.60466 0.90913 -5.065 4.09e-07 ***
## Desperation_Desire -0.23017 0.12439 -1.850 0.0643 .
## Desperation_Energy 0.26028 0.11669 2.231 0.0257 *
## Desperation_Comparison 0.25589 0.10681 2.396 0.0166 *
## Desperation_Overinvestment 0.07059 0.13242 0.533 0.5940
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Dspr_D Dspr_E Dspr_C
## Desprtn_Dsr -0.529
## Dsprtn_Enrg -0.067 -0.224
## Dsprtn_Cmpr -0.333 -0.225 0.037
## Dsprtn_Ovrn -0.295 -0.212 -0.279 -0.183## (Intercept) Desperation_Desire
## 0.01000508 0.79439797
## Desperation_Energy Desperation_Comparison
## 1.29729100 1.29160523
## Desperation_Overinvestment
## 1.0731396411.3.4 Response Time = Desperation Subconstructs
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula:
## rt ~ Desperation_Desire + Desperation_Energy + Desperation_Comparison +
## Desperation_Overinvestment + (1 | subj_idx)
## Data: regression_data
##
## REML criterion at convergence: 73127.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.337 -0.309 -0.124 0.078 44.001
##
## Random effects:
## Groups Name Variance Std.Dev.
## subj_idx (Intercept) 0.4614 0.6793
## Residual 1.2694 1.1267
## Number of obs: 23600, groups: subj_idx, 118
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 0.69849 0.34812 112.99997 2.006 0.0472 *
## Desperation_Desire -0.01658 0.04699 112.99997 -0.353 0.7248
## Desperation_Energy 0.04589 0.04477 112.99998 1.025 0.3075
## Desperation_Comparison 0.02382 0.04061 112.99998 0.587 0.5586
## Desperation_Overinvestment 0.04359 0.05092 112.99997 0.856 0.3938
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Dspr_D Dspr_E Dspr_C
## Desprtn_Dsr -0.538
## Dsprtn_Enrg -0.079 -0.215
## Dsprtn_Cmpr -0.333 -0.209 0.046
## Dsprtn_Ovrn -0.291 -0.209 -0.280 -0.19911.3.5 Display Clean Tables
| Overall Desperation | Subconstructs | |
|---|---|---|
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 | ||
| (Intercept) | 0.000*** | 0.010*** |
| (0.000) | (0.009) | |
| Desperation_Overall | 1.445+ | |
| (0.316) | ||
| normAttractive | 3.318*** | |
| (0.683) | ||
| Desperation_Overall × normAttractive | 0.995 | |
| (0.038) | ||
| Desperation_Desire | 0.794+ | |
| (0.099) | ||
| Desperation_Energy | 1.297* | |
| (0.151) | ||
| Desperation_Comparison | 1.292* | |
| (0.138) | ||
| Desperation_Overinvestment | 1.073 | |
| (0.142) | ||
| SD (Intercept subj_idx) | 1.745 | 1.678 |
| Num.Obs. | 23600 | 23600 |
| R2 Marg. | 0.128 | 0.056 |
| R2 Cond. | 0.547 | 0.491 |
| AIC | 9144.5 | 10098.8 |
| BIC | 9184.8 | 10147.2 |
| ICC | 0.5 | 0.5 |
| RMSE | 0.23 | 0.24 |
| Overall Desperation | Subconstructs | |
|---|---|---|
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 | ||
| (Intercept) | 0.477 | 0.698* |
| (0.368) | (0.348) | |
| Desperation_Overall | 0.039 | |
| (0.069) | ||
| normAttractive | 0.042 | |
| (0.053) | ||
| Desperation_Overall × normAttractive | 0.016 | |
| (0.010) | ||
| Desperation_Desire | -0.017 | |
| (0.047) | ||
| Desperation_Energy | 0.046 | |
| (0.045) | ||
| Desperation_Comparison | 0.024 | |
| (0.041) | ||
| Desperation_Overinvestment | 0.044 | |
| (0.051) | ||
| SD (Intercept subj_idx) | 0.664 | 0.679 |
| SD (Observations) | 1.123 | 1.127 |
| Num.Obs. | 23600 | 23600 |
| R2 Marg. | 0.011 | 0.007 |
| R2 Cond. | 0.267 | 0.272 |
| AIC | 72978.7 | 73141.7 |
| BIC | 73027.1 | 73198.2 |
| ICC | 0.3 | 0.3 |
| RMSE | 1.12 | 1.12 |
11.3.6 Trying the log of RT
11.3.6.1 Does it make sense to try log RT?
## # A tibble: 1 × 7
## N Mean_RT Median_RT SD_RT Min_RT Max_RT Skewness
## <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 23600 1.10 0.739 1.31 0.000476 50.8 10.1
## # A tibble: 20 × 2
## subj_idx rt
## <fct> <dbl>
## 1 442977 50.8
## 2 741132 49.3
## 3 607875 42.4
## 4 621879 29.4
## 5 607875 22.2
## 6 607875 22.2
## 7 607875 20.7
## 8 780214 20.2
## 9 621567 18.8
## 10 621567 18.6
## 11 621567 17.6
## 12 621879 17.2
## 13 607875 16.7
## 14 607875 16.7
## 15 258418 16.5
## 16 387581 16.3
## 17 621879 16.3
## 18 822671 16.2
## 19 621567 16.1
## 20 607875 15.4## # A tibble: 1 × 5
## Total_Trials Over_5s Over_10s Over_20s Percent_Over_10s
## <int> <int> <int> <int> <dbl>
## 1 23600 355 63 8 0.26711.3.6.2 Fitting the model
| Overall Desperation | Subconstructs | |
|---|---|---|
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 | ||
| (Intercept) | -0.651* | -0.606* |
| (0.256) | (0.272) | |
| Desperation_Overall | 0.083+ | |
| (0.048) | ||
| Desperation_Desire | -0.000 | |
| (0.037) | ||
| Desperation_Energy | 0.030 | |
| (0.035) | ||
| Desperation_Comparison | 0.021 | |
| (0.032) | ||
| Desperation_Overinvestment | 0.034 | |
| (0.040) | ||
| SD (Intercept subj_idx) | 0.527 | 0.533 |
| SD (Observations) | 0.512 | 0.512 |
| Num.Obs. | 23600 | 23600 |
| R2 Marg. | 0.013 | 0.015 |
| R2 Cond. | 0.521 | 0.527 |
| AIC | 26023.1 | 26044.1 |
| BIC | 26055.4 | 26100.6 |
| ICC | 0.5 | 0.5 |
| RMSE | 0.51 | 0.51 |
11.3.7 Yes/No = Face Attractiveness + Desperation
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: response ~ Desperation_c * Attractiveness_c + (1 + Attractiveness_c |
## subj_idx) + (1 | imageFile)
## Data: attractiveness_data
## Control: glmerControl(optimizer = "bobyqa")
##
## AIC BIC logLik -2*log(L) df.resid
## 8426.9 8491.4 -4205.4 8410.9 23592
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2488 -0.2059 -0.0893 -0.0355 19.7380
##
## Random effects:
## Groups Name Variance Std.Dev. Corr
## imageFile (Intercept) 1.14785 1.0714
## subj_idx (Intercept) 4.24235 2.0597
## Attractiveness_c 0.07446 0.2729 -0.68
## Number of obs: 23600, groups: imageFile, 430; subj_idx, 118
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.50898 0.21007 -21.464 <2e-16 ***
## Desperation_c 0.41984 0.19713 2.130 0.0332 *
## Attractiveness_c 1.58898 0.09320 17.050 <2e-16 ***
## Desperation_c:Attractiveness_c -0.05788 0.05291 -1.094 0.2740
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Dsprt_ Attrc_
## Desperatn_c -0.036
## Attrctvnss_ -0.274 0.011
## Dsprtn_c:A_ 0.028 -0.434 -0.04011.3.7.1 Table for Viewing Pleasure
| Attractiveness × Desperation | |
|---|---|
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 | |
| (Intercept) | -4.509*** |
| (0.210) | |
| Desperation_c | 0.420* |
| (0.197) | |
| Attractiveness_c | 1.589*** |
| (0.093) | |
| Desperation_c × Attractiveness_c | -0.058 |
| (0.053) | |
| SD (Intercept imageFile) | 1.071 |
| SD (Intercept subj_idx) | 2.060 |
| SD (Attractiveness_c subj_idx) | 0.273 |
| Cor (Intercept~Attractiveness_c subj_idx) | -0.677 |
| Num.Obs. | 23600 |
| R2 Marg. | 0.159 |
| R2 Cond. | 0.683 |
| AIC | 8426.9 |
| BIC | 8491.4 |
| ICC | 0.6 |
| RMSE | 0.21 |
11.3.7.2 Visualize the Interaction
## You are calculating adjusted predictions on the population-level (i.e.
## `type = "fixed"`) for a *generalized* linear mixed model.
## This may produce biased estimates due to Jensen's inequality. Consider
## setting `bias_correction = TRUE` to correct for this bias.
## See also the documentation of the `bias_correction` argument.
11.3.7.3 Trying the log RT
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Log_RT ~ Desperation_c * Attractiveness_c + (1 | subj_idx) +
## (1 | imageFile)
## Data: attractiveness_rt_data
##
## REML criterion at convergence: 35502.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -13.2942 -0.6152 -0.1162 0.4645 7.8983
##
## Random effects:
## Groups Name Variance Std.Dev.
## imageFile (Intercept) 0.007719 0.08786
## subj_idx (Intercept) 0.272250 0.52178
## Residual 0.251824 0.50182
## Number of obs: 23600, groups: imageFile, 430; subj_idx, 118
##
## Fixed effects:
## Estimate Std. Error df t value
## (Intercept) -2.118e-01 4.834e-02 1.177e+02 -4.381
## Desperation_c 8.234e-02 4.723e-02 1.158e+02 1.743
## Attractiveness_c 7.075e-02 7.311e-03 4.409e+02 9.678
## Desperation_c:Attractiveness_c 1.130e-02 4.432e-03 2.316e+04 2.551
## Pr(>|t|)
## (Intercept) 2.58e-05 ***
## Desperation_c 0.0839 .
## Attractiveness_c < 2e-16 ***
## Desperation_c:Attractiveness_c 0.0108 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Dsprt_ Attrc_
## Desperatn_c 0.000
## Attrctvnss_ 0.000 -0.002
## Dsprtn_c:A_ -0.001 0.000 -0.01311.3.7.4 Table for Viewing Pleasure
| Attractiveness × Desperation | |
|---|---|
| + p < 0.1, * p < 0.05, ** p < 0.01, *** p < 0.001 | |
| (Intercept) | -0.212*** |
| (0.048) | |
| Desperation_c | 0.082+ |
| (0.047) | |
| Attractiveness_c | 0.071*** |
| (0.007) | |
| Desperation_c × Attractiveness_c | 0.011* |
| (0.004) | |
| SD (Intercept imageFile) | 0.088 |
| SD (Intercept subj_idx) | 0.522 |
| SD (Observations) | 0.502 |
| Num.Obs. | 23600 |
| R2 Marg. | 0.019 |
| R2 Cond. | 0.535 |
| AIC | 35516.7 |
| BIC | 35573.2 |
| ICC | 0.5 |
| RMSE | 0.50 |
11.3.7.5 Visualize the interaction
