Labeling notes:
pers_simplified references a variable coded for EVERY
candidate.
targ_gend_f references a variable coded for the candidate’s
gender.
deiexpert_f references a variable our between-subjects
manipulations.
Snapshot of the dataset is below:
Manipulation Check
Regressions
Target Gender by DEI Expert Identity on Ranking
“I reverse-coded the ranking variable. So I coded ‘1’ ranking as ‘4’, ‘2’ ranking as ‘3’, and ‘4’ as ‘1’” So higher #’s means person was more likely to be picked.
Mixed-Model Anova comparing EVERY candidate to each other
Pairwise comparisons (grouped by btwn-subjects conditions)
Pairwise comparisons (NOT grouped by btwn-subjects conditions)
Estimated marginal means for ranking (grouped by person)
Multi-level model grouping candidates by gender (into ‘man’ and ‘woman’)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: rank_r ~ targ_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 6206
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.657 -0.829 0.000 0.829 1.657
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.00 0.0
## Residual 1.22 1.1
## Number of obs: 2040, groups: pid, 510
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.5343 0.0590 2034.0000 42.99 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.0686 0.0834 2034.0000 -0.82 0.41
## deiexpert_fNo one has DEI Quals. -0.0405 0.0852 2034.0000 -0.48 0.63
## deiexpert_fWoman Has DEI Quals. -0.3619 0.0835 2034.0000 -4.33 0.0000153585 ***
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.0810 0.1204 2034.0000 0.67 0.50
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 0.7237 0.1181 2034.0000 6.13 0.0000000011 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT d_ohDQ d_WHDQ tTohDQ
## trg_gnd_fWT -0.707
## dx_NohDEIQ. -0.692 0.489
## dxp_WHDEIQ. -0.706 0.499 0.489
## t__WT:_ohDQ 0.489 -0.692 -0.707 -0.346
## t__WT:_WHDQ 0.499 -0.706 -0.346 -0.707 0.489
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')
Target Gender by DEI Expert Identity on Voice Solicitation
Mixed-Model Anova comparing EVERY candidate to each other
Pairwise comparisons (grouped by btwn-subjects conditions)
Pairwise comparisons (NOT grouped by btwn-subjects conditions)
Estimated marginal means for voice solicitation (grouped by person)
Multi-level model grouping candidates by gender (into ‘man’ and ‘woman’)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vs ~ targ_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 7366
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.901 -0.617 0.065 0.671 2.253
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.549 0.741
## Residual 1.758 1.326
## Number of obs: 2040, groups: pid, 510
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.9686 0.0903 992.7333 54.99 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.0614 0.1002 1527.0000 -0.61 0.54007
## deiexpert_fNo one has DEI Quals. -0.1953 0.1305 992.7333 -1.50 0.13493
## deiexpert_fWoman Has DEI Quals. -0.8651 0.1280 992.7333 -6.76 0.00000000002334038 ***
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.5366 0.1448 1527.0000 3.71 0.00022 ***
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 1.1692 0.1420 1527.0000 8.24 0.00000000000000038 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT d_ohDQ d_WHDQ tTohDQ
## trg_gnd_fWT -0.555
## dx_NohDEIQ. -0.692 0.384
## dxp_WHDEIQ. -0.706 0.392 0.489
## t__WT:_ohDQ 0.384 -0.692 -0.555 -0.271
## t__WT:_WHDQ 0.392 -0.706 -0.271 -0.555 0.489
Target Gender by DEI Expert Identity on Voice Quality
Comparing EVERY candidate to each other
Mixed-Model Anova comparing EVERY candidate to each other
Pairwise comparisons (grouped by btwn-subjects conditions)
Pairwise comparisons (NOT grouped by btwn-subjects conditions)
Estimated marginal means for voice quality (grouped by person)
Grouping candidates by gender (into ‘man’ and ‘woman’)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vq ~ targ_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 7068
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.405 -0.608 0.069 0.671 2.518
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.503 0.709
## Residual 1.504 1.226
## Number of obs: 2040, groups: pid, 510
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.1314 0.0847 974.1096 60.59 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.1643 0.0927 1527.0000 -1.77 0.07656 .
## deiexpert_fNo one has DEI Quals. -0.1609 0.1224 974.1096 -1.32 0.18872
## deiexpert_fWoman Has DEI Quals. -0.8240 0.1199 974.1096 -6.87 0.0000000000114928 ***
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.5059 0.1339 1527.0000 3.78 0.00016 ***
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 1.0594 0.1313 1527.0000 8.07 0.0000000000000014 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT d_ohDQ d_WHDQ tTohDQ
## trg_gnd_fWT -0.547
## dx_NohDEIQ. -0.692 0.379
## dxp_WHDEIQ. -0.706 0.386 0.489
## t__WT:_ohDQ 0.379 -0.692 -0.547 -0.267
## t__WT:_WHDQ 0.386 -0.706 -0.267 -0.547 0.489
Exploratory analyses
Gender as a control
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vq ~ targ_gend_f * deiexpert_f + part_gend_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 6966
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.390 -0.595 0.067 0.667 2.489
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.493 0.702
## Residual 1.502 1.226
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.2089 0.1000 793.7601 52.08 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.1720 0.0932 1506.0000 -1.85 0.06519 .
## deiexpert_fNo one has DEI Quals. -0.1654 0.1228 964.0079 -1.35 0.17826
## deiexpert_fWoman Has DEI Quals. -0.8164 0.1202 962.5760 -6.79 0.0000000000196976 ***
## part_gend_fMale Participants -0.1148 0.0849 499.0000 -1.35 0.17720
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.5169 0.1349 1506.0000 3.83 0.00013 ***
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 1.0600 0.1320 1506.0000 8.03 0.0000000000000019 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT d_ohDQ d_WHDQ pr__MP tTohDQ
## trg_gnd_fWT -0.466
## dx_NohDEIQ. -0.590 0.380
## dxp_WHDEIQ. -0.623 0.387 0.488
## prt_gnd_fMP -0.530 0.000 0.007 0.047
## t__WT:_ohDQ 0.322 -0.691 -0.549 -0.268 0.000
## t__WT:_WHDQ 0.329 -0.706 -0.268 -0.549 0.000 0.488## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vs ~ targ_gend_f * deiexpert_f + part_gend_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 7266
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.8924 -0.6180 0.0567 0.6803 2.2501
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.54 0.735
## Residual 1.76 1.327
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.0276 0.1067 805.8442 47.13 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.0665 0.1009 1506.0000 -0.66 0.51019
## deiexpert_fNo one has DEI Quals. -0.2052 0.1312 982.5585 -1.56 0.11793
## deiexpert_fWoman Has DEI Quals. -0.8627 0.1285 981.0761 -6.72 0.00000000003168282 ***
## part_gend_fMale Participants -0.0767 0.0902 499.0000 -0.85 0.39582
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.5459 0.1461 1506.0000 3.74 0.00019 ***
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 1.1697 0.1429 1506.0000 8.18 0.00000000000000058 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT d_ohDQ d_WHDQ pr__MP tTohDQ
## trg_gnd_fWT -0.473
## dx_NohDEIQ. -0.591 0.385
## dxp_WHDEIQ. -0.624 0.393 0.488
## prt_gnd_fMP -0.528 0.000 0.007 0.046
## t__WT:_ohDQ 0.327 -0.691 -0.557 -0.271 0.000
## t__WT:_WHDQ 0.334 -0.706 -0.272 -0.556 0.000 0.488## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: rank ~ targ_gend_f * deiexpert_f + part_gend_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 6126
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.655 -0.827 0.000 0.827 1.655
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.00 0.0
## Residual 1.22 1.1
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.462427745664741430 0.067109240246918042 2004.999999983236875778 36.69 < 0.0000000000000002 ***
## targ_gend_fWoman Target 0.075144508670520277 0.083890331922972169 2004.999999972303385221 0.90 0.37
## deiexpert_fNo one has DEI Quals. 0.037572254335259063 0.085859893932625039 2004.999999982490180628 0.44 0.66
## deiexpert_fWoman Has DEI Quals. 0.363153649684096247 0.084077939275502292 2004.999999990621518009 4.32 0.0000164205 ***
## part_gend_fMale Participants -0.000000000000000983 0.050269986224358854 2004.999999975920900397 0.00 1.00
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. -0.075144508670520249 0.121421995550262882 2004.999999973292233335 -0.62 0.54
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. -0.726307299368194714 0.118811160201283864 2004.999999982992903824 -6.11 0.0000000012 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT d_ohDQ d_WHDQ pr__MP tTohDQ
## trg_gnd_fWT -0.625
## dx_NohDEIQ. -0.614 0.489
## dxp_WHDEIQ. -0.642 0.499 0.488
## prt_gnd_fMP -0.468 0.000 0.006 0.040
## t__WT:_ohDQ 0.432 -0.691 -0.707 -0.345 0.000
## t__WT:_WHDQ 0.441 -0.706 -0.345 -0.707 0.000 0.488
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Part. gender as a moderator
Each candidate individually
VQ
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vq ~ pers_simplified * part_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 6663
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.841 -0.528 0.044 0.606 3.347
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.565 0.752
## Residual 1.219 1.104
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.8000 0.1657 1527.9848 35.01 < 0.0000000000000002 ***
## pers_simplifiedM2(PA) -1.4846 0.1937 1491.0000 -7.67 0.000000000000032 ***
## pers_simplifiedW1(JC) -1.0846 0.1937 1491.0000 -5.60 0.000000025464041 ***
## pers_simplifiedW2(PM) -0.4692 0.1937 1491.0000 -2.42 0.01552 *
## part_gend_fMale Participants 0.0102 0.2097 1527.9848 0.05 0.96127
## deiexpert_fNo one has DEI Quals. -0.6607 0.2381 1527.9848 -2.77 0.00560 **
## deiexpert_fWoman Has DEI Quals. -1.6618 0.2257 1527.9848 -7.36 0.000000000000291 ***
## pers_simplifiedM2(PA):part_gend_fMale Participants 0.2346 0.2451 1491.0000 0.96 0.33866
## pers_simplifiedW1(JC):part_gend_fMale Participants -0.0589 0.2451 1491.0000 -0.24 0.81013
## pers_simplifiedW2(PM):part_gend_fMale Participants -0.1465 0.2451 1491.0000 -0.60 0.55014
## pers_simplifiedM2(PA):deiexpert_fNo one has DEI Quals. 1.2961 0.2784 1491.0000 4.66 0.000003506417507 ***
## pers_simplifiedW1(JC):deiexpert_fNo one has DEI Quals. 0.9699 0.2784 1491.0000 3.48 0.00051 ***
## pers_simplifiedW2(PM):deiexpert_fNo one has DEI Quals. 1.3053 0.2784 1491.0000 4.69 0.000002991724837 ***
## pers_simplifiedM2(PA):deiexpert_fWoman Has DEI Quals. 1.6622 0.2638 1491.0000 6.30 0.000000000388281 ***
## pers_simplifiedW1(JC):deiexpert_fWoman Has DEI Quals. 1.4925 0.2638 1491.0000 5.66 0.000000018370170 ***
## pers_simplifiedW2(PM):deiexpert_fWoman Has DEI Quals. 2.7784 0.2638 1491.0000 10.53 < 0.0000000000000002 ***
## part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.1908 0.3027 1527.9848 -0.63 0.52863
## part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.1642 0.2933 1527.9848 0.56 0.57581
## pers_simplifiedM2(PA):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.1079 0.3538 1491.0000 -0.31 0.76035
## pers_simplifiedW1(JC):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. 0.0860 0.3538 1491.0000 0.24 0.80793
## pers_simplifiedW2(PM):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.1122 0.3538 1491.0000 -0.32 0.75113
## pers_simplifiedM2(PA):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.2195 0.3429 1491.0000 -0.64 0.52209
## pers_simplifiedW1(JC):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.1667 0.3429 1491.0000 -0.49 0.62691
## pers_simplifiedW2(PM):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.9804 0.3429 1491.0000 -2.86 0.00430 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
VS
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vs ~ pers_simplified * part_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 7000
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.390 -0.564 0.052 0.646 2.802
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.613 0.783
## Residual 1.469 1.212
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.7538 0.1790 1577.7069 32.15 < 0.0000000000000002 ***
## pers_simplifiedM2(PA) -1.8308 0.2126 1491.0000 -8.61 < 0.0000000000000002 ***
## pers_simplifiedW1(JC) -1.0769 0.2126 1491.0000 -5.07 0.000000456990093 ***
## pers_simplifiedW2(PM) -0.5692 0.2126 1491.0000 -2.68 0.00749 **
## part_gend_fMale Participants -0.0779 0.2265 1577.7069 -0.34 0.73086
## deiexpert_fNo one has DEI Quals. -0.9014 0.2572 1577.7069 -3.50 0.00047 ***
## deiexpert_fWoman Has DEI Quals. -1.8591 0.2437 1577.7069 -7.63 0.000000000000041 ***
## pers_simplifiedM2(PA):part_gend_fMale Participants 0.6085 0.2690 1491.0000 2.26 0.02385 *
## pers_simplifiedW1(JC):part_gend_fMale Participants 0.1140 0.2690 1491.0000 0.42 0.67194
## pers_simplifiedW2(PM):part_gend_fMale Participants -0.0141 0.2690 1491.0000 -0.05 0.95820
## pers_simplifiedM2(PA):deiexpert_fNo one has DEI Quals. 1.6996 0.3055 1491.0000 5.56 0.000000031380415 ***
## pers_simplifiedW1(JC):deiexpert_fNo one has DEI Quals. 1.2654 0.3055 1491.0000 4.14 0.000036370873570 ***
## pers_simplifiedW2(PM):deiexpert_fNo one has DEI Quals. 1.6348 0.3055 1491.0000 5.35 0.000000101198158 ***
## pers_simplifiedM2(PA):deiexpert_fWoman Has DEI Quals. 2.0413 0.2895 1491.0000 7.05 0.000000000002729 ***
## pers_simplifiedW1(JC):deiexpert_fWoman Has DEI Quals. 1.7480 0.2895 1491.0000 6.04 0.000000001979754 ***
## pers_simplifiedW2(PM):deiexpert_fWoman Has DEI Quals. 3.1219 0.2895 1491.0000 10.78 < 0.0000000000000002 ***
## part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. 0.0502 0.3269 1577.7069 0.15 0.87797
## part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.3290 0.3168 1577.7069 1.04 0.29918
## pers_simplifiedM2(PA):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.5908 0.3884 1491.0000 -1.52 0.12840
## pers_simplifiedW1(JC):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.3437 0.3884 1491.0000 -0.89 0.37627
## pers_simplifiedW2(PM):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.4329 0.3884 1491.0000 -1.11 0.26515
## pers_simplifiedM2(PA):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.6732 0.3763 1491.0000 -1.79 0.07383 .
## pers_simplifiedW1(JC):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.4152 0.3763 1491.0000 -1.10 0.27007
## pers_simplifiedW2(PM):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -1.1948 0.3763 1491.0000 -3.17 0.00153 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Ranking
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: rank ~ pers_simplified * part_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 5936
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.0455 -0.8652 0.0147 0.9144 2.4847
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.0 0.00
## Residual 1.1 1.05
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.2769 0.1301 1988.0000 17.51 < 0.0000000000000002 ***
## pers_simplifiedM2(PA) 0.5077 0.1839 1988.0000 2.76 0.00583 **
## pers_simplifiedW1(JC) 0.7077 0.1839 1988.0000 3.85 0.00012 ***
## pers_simplifiedW2(PM) -0.3231 0.1839 1988.0000 -1.76 0.07914 .
## part_gend_fMale Participants -0.0269 0.1646 1988.0000 -0.16 0.87009
## deiexpert_fNo one has DEI Quals. 0.0346 0.1869 1988.0000 0.18 0.85336
## deiexpert_fWoman Has DEI Quals. 0.8678 0.1771 1988.0000 4.90 0.000001042 ***
## pers_simplifiedM2(PA):part_gend_fMale Participants -0.1651 0.2328 1988.0000 -0.71 0.47826
## pers_simplifiedW1(JC):part_gend_fMale Participants 0.0238 0.2328 1988.0000 0.10 0.91861
## pers_simplifiedW2(PM):part_gend_fMale Participants 0.2490 0.2328 1988.0000 1.07 0.28489
## pers_simplifiedM2(PA):deiexpert_fNo one has DEI Quals. -0.2126 0.2643 1988.0000 -0.80 0.42131
## pers_simplifiedW1(JC):deiexpert_fNo one has DEI Quals. 0.0136 0.2643 1988.0000 0.05 0.95891
## pers_simplifiedW2(PM):deiexpert_fNo one has DEI Quals. 0.0608 0.2643 1988.0000 0.23 0.81816
## pers_simplifiedM2(PA):deiexpert_fWoman Has DEI Quals. -0.8366 0.2505 1988.0000 -3.34 0.00085 ***
## pers_simplifiedW1(JC):deiexpert_fWoman Has DEI Quals. -1.2077 0.2505 1988.0000 -4.82 0.000001539 ***
## pers_simplifiedW2(PM):deiexpert_fWoman Has DEI Quals. -1.4269 0.2505 1988.0000 -5.70 0.000000014 ***
## part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. 0.2412 0.2376 1988.0000 1.02 0.31010
## part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.3886 0.2302 1988.0000 -1.69 0.09157 .
## pers_simplifiedM2(PA):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.1300 0.3360 1988.0000 -0.39 0.69891
## pers_simplifiedW1(JC):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.3637 0.3360 1988.0000 -1.08 0.27926
## pers_simplifiedW2(PM):part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.4712 0.3360 1988.0000 -1.40 0.16093
## pers_simplifiedM2(PA):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.4420 0.3256 1988.0000 1.36 0.17483
## pers_simplifiedW1(JC):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.3929 0.3256 1988.0000 1.21 0.22774
## pers_simplifiedW2(PM):part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.7197 0.3256 1988.0000 2.21 0.02719 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')
Combined men and women
VQ
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vq ~ targ_gend_f * part_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 6956
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.421 -0.595 0.084 0.654 2.557
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.498 0.705
## Residual 1.490 1.221
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.0577 0.1383 955.7883 36.58 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.0346 0.1514 1503.0000 -0.23 0.819
## part_gend_fMale Participants 0.1275 0.1750 955.7883 0.73 0.466
## deiexpert_fNo one has DEI Quals. -0.0126 0.1987 955.7883 -0.06 0.949
## deiexpert_fWoman Has DEI Quals. -0.8307 0.1883 955.7883 -4.41 0.00001145302 ***
## targ_gend_fWoman Target:part_gend_fMale Participants -0.2200 0.1916 1503.0000 -1.15 0.251
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.4895 0.2176 1503.0000 2.25 0.025 *
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 1.3044 0.2062 1503.0000 6.32 0.00000000033 ***
## part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.2447 0.2526 955.7883 -0.97 0.333
## part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.0544 0.2448 955.7883 0.22 0.824
## targ_gend_fWoman Target:part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. 0.0409 0.2766 1503.0000 0.15 0.883
## targ_gend_fWoman Target:part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.4638 0.2681 1503.0000 -1.73 0.084 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT pr__MP d_ohDQ d_WHDQ t__WTP tTohDQ t_THDQ pPohDQ p_PHDQ tTPohDQ
## trg_gnd_fWT -0.548
## prt_gnd_fMP -0.790 0.433
## dx_NohDEIQ. -0.696 0.381 0.550
## dxp_WHDEIQ. -0.734 0.402 0.580 0.511
## tr__WT:__MP 0.433 -0.790 -0.548 -0.301 -0.318
## t__WT:_ohDQ 0.381 -0.696 -0.301 -0.548 -0.280 0.550
## t__WT:_WHDQ 0.402 -0.734 -0.318 -0.280 -0.548 0.580 0.511
## p__MP:_ohDQ 0.547 -0.300 -0.693 -0.787 -0.402 0.379 0.431 0.220
## p__MP:_WHDQ 0.565 -0.309 -0.715 -0.393 -0.769 0.391 0.215 0.421 0.495
## t__WT:PohDQ -0.300 0.547 0.379 0.431 0.220 -0.693 -0.787 -0.402 -0.548 -0.271
## t__WT:_PHDQ -0.309 0.565 0.391 0.215 0.421 -0.715 -0.393 -0.769 -0.271 -0.548 0.495
VS
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: vs ~ targ_gend_f * part_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 7254
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.9895 -0.6036 0.0668 0.6880 2.3977
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.544 0.737
## Residual 1.746 1.321
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.8385 0.1476 974.3667 32.78 < 0.0000000000000002 ***
## targ_gend_fWoman Target 0.0923 0.1639 1503.0000 0.56 0.573
## part_gend_fMale Participants 0.2263 0.1868 974.3667 1.21 0.226
## deiexpert_fNo one has DEI Quals. -0.0516 0.2122 974.3667 -0.24 0.808
## deiexpert_fWoman Has DEI Quals. -0.8385 0.2011 974.3667 -4.17 0.00003318043 ***
## targ_gend_fWoman Target:part_gend_fMale Participants -0.2543 0.2074 1503.0000 -1.23 0.220
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.6003 0.2355 1503.0000 2.55 0.011 *
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. 1.4143 0.2232 1503.0000 6.34 0.00000000031 ***
## part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.2452 0.2697 974.3667 -0.91 0.363
## part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.0076 0.2613 974.3667 -0.03 0.977
## targ_gend_fWoman Target:part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.0929 0.2994 1503.0000 -0.31 0.756
## targ_gend_fWoman Target:part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.4684 0.2901 1503.0000 -1.61 0.107
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT pr__MP d_ohDQ d_WHDQ t__WTP tTohDQ t_THDQ pPohDQ p_PHDQ tTPohDQ
## trg_gnd_fWT -0.555
## prt_gnd_fMP -0.790 0.439
## dx_NohDEIQ. -0.696 0.386 0.550
## dxp_WHDEIQ. -0.734 0.408 0.580 0.511
## tr__WT:__MP 0.439 -0.790 -0.555 -0.305 -0.322
## t__WT:_ohDQ 0.386 -0.696 -0.305 -0.555 -0.284 0.550
## t__WT:_WHDQ 0.408 -0.734 -0.322 -0.284 -0.555 0.580 0.511
## p__MP:_ohDQ 0.547 -0.304 -0.693 -0.787 -0.402 0.385 0.437 0.223
## p__MP:_WHDQ 0.565 -0.314 -0.715 -0.393 -0.769 0.397 0.218 0.427 0.495
## t__WT:PohDQ -0.304 0.547 0.385 0.437 0.223 -0.693 -0.787 -0.402 -0.555 -0.275
## t__WT:_PHDQ -0.314 0.565 0.397 0.218 0.427 -0.715 -0.393 -0.769 -0.275 -0.555 0.495
Ranking
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: rank ~ targ_gend_f * part_gend_f * deiexpert_f + (1 | pid)
## Data: qual_clean_long
##
## REML criterion at convergence: 6123
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.798 -0.899 0.000 0.899 1.798
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.00 0.0
## Residual 1.21 1.1
## Number of obs: 2012, groups: pid, 503
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.5308 0.0966 2000.0000 26.20 < 0.0000000000000002 ***
## targ_gend_fWoman Target -0.0615 0.1366 2000.0000 -0.45 0.65238
## part_gend_fMale Participants -0.1095 0.1222 2000.0000 -0.90 0.37060
## deiexpert_fNo one has DEI Quals. -0.0718 0.1388 2000.0000 -0.52 0.60528
## deiexpert_fWoman Has DEI Quals. 0.4495 0.1316 2000.0000 3.42 0.00065 ***
## targ_gend_fWoman Target:part_gend_fMale Participants 0.2189 0.1729 2000.0000 1.27 0.20549
## targ_gend_fWoman Target:deiexpert_fNo one has DEI Quals. 0.1435 0.1963 2000.0000 0.73 0.46486
## targ_gend_fWoman Target:deiexpert_fWoman Has DEI Quals. -0.8990 0.1860 2000.0000 -4.83 0.0000015 ***
## part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. 0.1762 0.1765 2000.0000 1.00 0.31804
## part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. -0.1677 0.1710 2000.0000 -0.98 0.32693
## targ_gend_fWoman Target:part_gend_fMale Participants:deiexpert_fNo one has DEI Quals. -0.3525 0.2495 2000.0000 -1.41 0.15797
## targ_gend_fWoman Target:part_gend_fMale Participants:deiexpert_fWoman Has DEI Quals. 0.3353 0.2418 2000.0000 1.39 0.16568
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tr__WT pr__MP d_ohDQ d_WHDQ t__WTP tTohDQ t_THDQ pPohDQ p_PHDQ tTPohDQ
## trg_gnd_fWT -0.707
## prt_gnd_fMP -0.790 0.559
## dx_NohDEIQ. -0.696 0.492 0.550
## dxp_WHDEIQ. -0.734 0.519 0.580 0.511
## tr__WT:__MP 0.559 -0.790 -0.707 -0.389 -0.410
## t__WT:_ohDQ 0.492 -0.696 -0.389 -0.707 -0.361 0.550
## t__WT:_WHDQ 0.519 -0.734 -0.410 -0.361 -0.707 0.580 0.511
## p__MP:_ohDQ 0.547 -0.387 -0.693 -0.787 -0.402 0.490 0.556 0.284
## p__MP:_WHDQ 0.565 -0.399 -0.715 -0.393 -0.769 0.506 0.278 0.544 0.495
## t__WT:PohDQ -0.387 0.547 0.490 0.556 0.284 -0.693 -0.787 -0.402 -0.707 -0.350
## t__WT:_PHDQ -0.399 0.565 0.506 0.278 0.544 -0.715 -0.393 -0.769 -0.350 -0.707 0.495
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## [[1]]
##
## [[2]]
##
## [[3]]
##
## [[4]]
Rank woman as #1
Here, I compare whether participants ranked a woman as N# 1 (regardless of condition)
##
## Call:
## lm(formula = rank_wom ~ deiexpert, data = qual_clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.793 -0.297 0.207 0.429 0.703
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2971 0.0343 8.66 < 0.0000000000000002 ***
## deiexpertnone 0.2743 0.0496 5.53 0.000000051 ***
## deiexpertwoman 0.4960 0.0486 10.20 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.454 on 507 degrees of freedom
## Multiple R-squared: 0.171, Adjusted R-squared: 0.168
## F-statistic: 52.2 on 2 and 507 DF, p-value: <0.0000000000000002