Participant Info
Gender
##
## Man NonBinary Woman
## 0.328125000 0.004464286 0.417410714Age
## [1] 36.28869## [1] 11.15013Status Information
Median
## [1] 5Mean
## [1] 4.681154SD’s within participants
Reliabilities
Mutability
Voicing
Voicing futility
Status Futility
Status
Status Breakdown
Number of participants who reported having “high” status
##
## High Low
## 715 394Distribution of status levels across participants
Graph of distribution
Mutability breakdown
Mean, median, sd of mutability across participants
Graph of distribution
Relationship between Mutability, Status, and Voice
Linear Models
Status (Continuous)
Voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice ~ status + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3415.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9005 -0.4375 0.0726 0.5016 2.8812
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.4799 0.6927
## team (Intercept) 0.0000 0.0000
## Residual 0.9390 0.9690
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.10500 0.11100 1015.92320 18.96 <0.0000000000000002 ***
## status 0.60975 0.02141 1106.27485 28.49 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## status -0.902
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice ~ status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3228.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9084 -0.4423 0.0796 0.4917 2.8050
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.459853 0.67812
## team (Intercept) 0.003893 0.06239
## Residual 0.927323 0.96298
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.904432 0.198663 192.638248 9.586 <0.0000000000000002 ***
## status 0.605980 0.022133 1030.137097 27.379 <0.0000000000000002 ***
## age 0.004951 0.004348 325.699356 1.139 0.256
## gender_textNonBinary 0.801258 0.653464 396.375966 1.226 0.221
## gender_textWoman -0.055953 0.098870 328.360453 -0.566 0.572
## monthssince -0.003419 0.003886 1000.206951 -0.880 0.379
## monthsjoined 0.004395 0.002711 983.282767 1.621 0.105
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) status age gnd_NB gndr_W mnthss
## status -0.464
## age -0.701 -0.095
## gndr_txtNnB -0.086 0.055 0.015
## gndr_txtWmn -0.235 0.060 -0.120 0.085
## monthssince -0.088 0.135 -0.020 -0.023 -0.011
## monthsjoind -0.144 -0.072 -0.046 0.030 0.109 -0.425Status Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futstatus ~ status + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3948.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2432 -0.5509 -0.0974 0.4937 3.7875
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.1611582 1.07757
## team (Intercept) 0.0002977 0.01725
## Residual 1.3697295 1.17035
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.30502 0.14457 420.18646 29.778 <0.0000000000000002 ***
## status -0.27108 0.02712 1089.39317 -9.997 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## status -0.877## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futstatus ~ status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3742.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2863 -0.5578 -0.0966 0.5017 3.8642
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.21203 1.10092
## team (Intercept) 0.00464 0.06812
## Residual 1.34362 1.15915
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.4651931 0.2811428 400.3355134 15.882 <0.0000000000000002 ***
## status -0.2767957 0.0281766 1013.9008297 -9.824 <0.0000000000000002 ***
## age 0.0004011 0.0064084 323.0062926 0.063 0.950
## gender_textNonBinary -0.4877791 0.9474066 369.9479977 -0.515 0.607
## gender_textWoman -0.1668570 0.1456063 325.4329441 -1.146 0.253
## monthssince -0.0038606 0.0050183 1037.8684803 -0.769 0.442
## monthsjoined -0.0003411 0.0035113 1036.1453019 -0.097 0.923
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) status age gnd_NB gndr_W mnthss
## status -0.412
## age -0.747 -0.082
## gndr_txtNnB -0.085 0.049 0.019
## gndr_txtWmn -0.231 0.050 -0.117 0.085
## monthssince -0.080 0.144 -0.018 -0.021 -0.010
## monthsjoind -0.124 -0.093 -0.038 0.025 0.095 -0.437Task Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futtask ~ status + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3993.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0307 -0.5625 -0.1124 0.5388 4.6233
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.829 0.9105
## team (Intercept) 0.000 0.0000
## Residual 1.574 1.2548
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.5921 0.1443 1017.9454 31.82 <0.0000000000000002 ***
## status -0.3722 0.0278 1106.6903 -13.39 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## status -0.901
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futtask ~ status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3792.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.0516 -0.5543 -0.1080 0.5199 4.6603
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.8649 0.930
## team (Intercept) 0.0000 0.000
## Residual 1.5677 1.252
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.85968603 0.26181073 471.61512311 18.562 <0.0000000000000002 ***
## status -0.37151196 0.02907110 1037.98322526 -12.779 <0.0000000000000002 ***
## age -0.00641042 0.00584429 324.28716845 -1.097 0.274
## gender_textNonBinary -0.50799566 0.87550429 390.14624449 -0.580 0.562
## gender_textWoman -0.05698376 0.13287728 326.92730482 -0.429 0.668
## monthssince 0.00189111 0.00511345 1012.83776836 0.370 0.712
## monthsjoined -0.00007458 0.00356503 1001.82124969 -0.021 0.983
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) status age gnd_NB gndr_W mnthss
## status -0.461
## age -0.718 -0.093
## gndr_txtNnB -0.087 0.054 0.016
## gndr_txtWmn -0.237 0.058 -0.120 0.085
## monthssince -0.087 0.137 -0.020 -0.022 -0.011
## monthsjoind -0.144 -0.077 -0.045 0.028 0.107 -0.426
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Voice (Prohibitive)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.proh ~ status + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3841.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.1114 -0.5268 0.0687 0.5094 3.5347
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.092 1.045
## team (Intercept) 0.000 0.000
## Residual 1.231 1.110
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.83429 0.13773 1043.96692 13.32 <0.0000000000000002 ***
## status 0.56377 0.02581 1084.91893 21.84 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## status -0.877
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.proh ~ status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3608.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.1349 -0.5196 0.0664 0.4986 3.3344
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.0736864519268 1.03618842
## team (Intercept) 0.0000000004463 0.00002113
## Residual 1.1813846436319 1.08691520
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.092072 0.262078 436.702662 7.983 0.0000000000000128 ***
## status 0.557833 0.026433 1014.005037 21.104 < 0.0000000000000002 ***
## age -0.001880 0.006026 311.313191 -0.312 0.755198
## gender_textNonBinary 0.006200 0.890579 357.055550 0.007 0.994449
## gender_textWoman -0.472620 0.136907 313.690897 -3.452 0.000632 ***
## monthssince -0.001248 0.004705 1037.762298 -0.265 0.790908
## monthsjoined 0.006867 0.003289 1037.618126 2.088 0.037067 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) status age gnd_NB gndr_W mnthss
## status -0.415
## age -0.754 -0.082
## gndr_txtNnB -0.085 0.049 0.019
## gndr_txtWmn -0.233 0.050 -0.117 0.085
## monthssince -0.080 0.145 -0.018 -0.020 -0.010
## monthsjoind -0.126 -0.094 -0.038 0.024 0.095 -0.437
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Voice (Promotive)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.prom ~ status + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3592.7
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.4661 -0.5310 0.0973 0.5450 3.2020
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.458470 0.67710
## team (Intercept) 0.004256 0.06524
## Residual 1.150151 1.07245
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.99974 0.12367 97.07227 16.17 <0.0000000000000002 ***
## status 0.62063 0.02313 1094.99597 26.83 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## status -0.875## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.prom ~ status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3421.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.3888 -0.5116 0.1118 0.5636 3.1694
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.441978 0.66481
## team (Intercept) 0.004917 0.07012
## Residual 1.171431 1.08233
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.851536 0.209764 302.422830 8.827 <0.0000000000000002 ***
## status 0.614872 0.024224 1024.712761 25.383 <0.0000000000000002 ***
## age 0.002187 0.004515 319.501895 0.484 0.629
## gender_textNonBinary 0.700106 0.684186 401.495041 1.023 0.307
## gender_textWoman -0.008759 0.102703 322.149572 -0.085 0.932
## monthssince 0.002018 0.004226 959.389362 0.478 0.633
## monthsjoined 0.004721 0.002944 942.371262 1.603 0.109
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) status age gnd_NB gndr_W mnthss
## status -0.483
## age -0.682 -0.100
## gndr_txtNnB -0.086 0.057 0.013
## gndr_txtWmn -0.236 0.064 -0.122 0.085
## monthssince -0.091 0.131 -0.021 -0.024 -0.011
## monthsjoind -0.152 -0.063 -0.050 0.031 0.115 -0.419Mutability
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: hiermut ~ status + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3603
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.06895 -0.49579 0.04914 0.51877 2.96039
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.7773930664200843221 0.88169896587
## team (Intercept) 0.0000000000000006559 0.00000002561
## Residual 1.0277963709611335208 1.01380292511
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.47028 0.12285 1038.72661 20.11 <0.0000000000000002 ***
## status 0.38343 0.02325 1097.35528 16.49 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## status -0.885
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: hiermut ~ status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3387.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1268 -0.4974 0.0337 0.5240 3.1818
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.7503 0.8662
## team (Intercept) 0.0000 0.0000
## Residual 0.9956 0.9978
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.919122 0.227394 450.733197 12.837 <0.0000000000000002 ***
## status 0.398756 0.023860 1028.328491 16.712 <0.0000000000000002 ***
## age -0.011478 0.005170 316.159302 -2.220 0.0271 *
## gender_textNonBinary 0.665163 0.767808 368.962908 0.866 0.3869
## gender_textWoman -0.050870 0.117499 318.656029 -0.433 0.6653
## monthssince 0.008513 0.004228 1035.296703 2.013 0.0443 *
## monthsjoined -0.007517 0.002953 1030.521709 -2.546 0.0111 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) status age gnd_NB gndr_W mnthss
## status -0.433
## age -0.740 -0.086
## gndr_txtNnB -0.086 0.051 0.018
## gndr_txtWmn -0.235 0.053 -0.118 0.085
## monthssince -0.083 0.142 -0.019 -0.021 -0.010
## monthsjoind -0.133 -0.088 -0.041 0.026 0.100 -0.433
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Status (binary)
Voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice ~ highlowstat + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3685.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1990 -0.5043 0.1371 0.5374 2.7162
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.616 0.7849
## team (Intercept) 0.000 0.0000
## Residual 1.200 1.0957
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.54157 0.06173 477.28192 89.78 <0.0000000000000002 ***
## highlowstatLow -1.63932 0.08276 1099.07474 -19.81 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## highlwsttLw -0.478
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice ~ highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3487.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1722 -0.5225 0.1216 0.5641 2.5878
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.5887 0.7673
## team (Intercept) 0.0000 0.0000
## Residual 1.1965 1.0938
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.179534 0.200045 358.872671 25.892 <0.0000000000000002 ***
## highlowstatLow -1.606317 0.085726 1031.531308 -18.738 <0.0000000000000002 ***
## age 0.009500 0.004918 323.180779 1.932 0.0543 .
## gender_textNonBinary -0.025366 0.739470 394.198166 -0.034 0.9727
## gender_textWoman -0.100432 0.112008 327.163801 -0.897 0.3706
## monthssince -0.008566 0.004394 999.785000 -1.949 0.0515 .
## monthsjoined 0.006580 0.003067 988.999557 2.145 0.0322 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hghlwL age gnd_NB gndr_W mnthss
## highlwsttLw -0.198
## age -0.854 0.074
## gndr_txtNnB -0.066 -0.011 0.020
## gndr_txtWmn -0.222 -0.056 -0.119 0.082
## monthssince -0.005 -0.114 -0.016 -0.029 -0.013
## monthsjoind -0.214 0.059 -0.049 0.032 0.110 -0.422
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Status Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futstatus ~ highlowstat + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3989.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2376 -0.5810 -0.1252 0.5085 3.5452
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.1876488 1.08979
## team (Intercept) 0.0004037 0.02009
## Residual 1.4308267 1.19617
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.79250 0.07810 46.49505 35.756 < 0.0000000000000002 ***
## highlowstatLow 0.68620 0.09384 1059.03000 7.312 0.000000000000518 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## highlwsttLw -0.429## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futstatus ~ highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3785.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.2643 -0.5685 -0.1265 0.5190 3.5300
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.232796 1.11031
## team (Intercept) 0.004315 0.06569
## Residual 1.415875 1.18991
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.009755 0.263449 314.937710 11.424 < 0.0000000000000002 ***
## highlowstatLow 0.669047 0.097562 985.822628 6.858 0.0000000000123 ***
## age -0.001938 0.006484 321.188564 -0.299 0.765
## gender_textNonBinary -0.102945 0.959700 369.492353 -0.107 0.915
## gender_textWoman -0.142821 0.147519 324.780028 -0.968 0.334
## monthssince -0.001020 0.005117 1037.998691 -0.199 0.842
## monthsjoined -0.001749 0.003584 1035.545971 -0.488 0.626
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hghlwL age gnd_NB gndr_W mnthss
## highlwsttLw -0.175
## age -0.857 0.064
## gndr_txtNnB -0.068 -0.010 0.022
## gndr_txtWmn -0.220 -0.047 -0.116 0.083
## monthssince -0.001 -0.124 -0.014 -0.027 -0.012
## monthsjoind -0.191 0.075 -0.042 0.029 0.098 -0.434Task Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futtask ~ highlowstat + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 4078.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.3870 -0.5770 -0.1586 0.5326 3.7856
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.8917 0.9443
## team (Intercept) 0.0000 0.0000
## Residual 1.7054 1.3059
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.53191 0.07393 477.48893 34.245 <0.0000000000000002 ***
## highlowstatLow 0.89475 0.09880 1098.15253 9.056 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## highlwsttLw -0.476
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futtask ~ highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3874.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.3650 -0.5719 -0.1605 0.5201 3.7927
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.9161 0.9571
## team (Intercept) 0.0000 0.0000
## Residual 1.7104 1.3078
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.918462 0.245226 358.089055 11.901 < 0.0000000000000002 ***
## highlowstatLow 0.858603 0.103209 1027.500781 8.319 0.000000000000000279 ***
## age -0.009734 0.006037 322.627519 -1.612 0.108
## gender_textNonBinary 0.013289 0.905446 389.966441 0.015 0.988
## gender_textWoman -0.020455 0.137472 326.571938 -0.149 0.882
## monthssince 0.005800 0.005308 1009.723625 1.093 0.275
## monthsjoined -0.001672 0.003706 1000.002423 -0.451 0.652
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hghlwL age gnd_NB gndr_W mnthss
## highlwsttLw -0.195
## age -0.856 0.072
## gndr_txtNnB -0.066 -0.011 0.020
## gndr_txtWmn -0.222 -0.055 -0.119 0.082
## monthssince -0.004 -0.116 -0.016 -0.028 -0.012
## monthsjoind -0.211 0.061 -0.048 0.032 0.109 -0.424
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Voice (Prohibitive)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.proh ~ highlowstat + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 4014.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6411 -0.5027 0.0587 0.5341 3.1609
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.251 1.119
## team (Intercept) 0.000 0.000
## Residual 1.452 1.205
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.00006 0.07884 447.65284 63.42 <0.0000000000000002 ***
## highlowstatLow -1.48278 0.09479 1053.47081 -15.64 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## highlwsttLw -0.429
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.proh ~ highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3774.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6547 -0.5228 0.0577 0.5448 2.7638
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.2492202623863 1.11768523
## team (Intercept) 0.0000000003619 0.00001902
## Residual 1.3932416770099 1.18035659
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.074925 0.261789 342.319711 19.386 < 0.0000000000000002 ***
## highlowstatLow -1.449915 0.096956 981.689681 -14.954 < 0.0000000000000002 ***
## age 0.002404 0.006502 310.257181 0.370 0.711880
## gender_textNonBinary -0.768505 0.961542 356.634001 -0.799 0.424681
## gender_textWoman -0.514422 0.147912 313.754611 -3.478 0.000577 ***
## monthssince -0.006084 0.005088 1037.884597 -1.196 0.232080
## monthsjoined 0.009236 0.003561 1037.643550 2.593 0.009637 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hghlwL age gnd_NB gndr_W mnthss
## highlwsttLw -0.176
## age -0.865 0.063
## gndr_txtNnB -0.069 -0.010 0.022
## gndr_txtWmn -0.222 -0.046 -0.116 0.083
## monthssince 0.000 -0.125 -0.014 -0.026 -0.011
## monthsjoind -0.193 0.077 -0.041 0.028 0.097 -0.435
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Voice (Promotive)
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.prom ~ highlowstat + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3876
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6772 -0.5684 0.1668 0.5712 2.8829
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.6089752 0.78037
## team (Intercept) 0.0009129 0.03021
## Residual 1.4834229 1.21796
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.47029 0.06686 14.85559 81.81 <0.0000000000000002 ***
## highlowstatLow -1.57221 0.09034 1106.12207 -17.40 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## highlwsttLw -0.482## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.prom ~ highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3685.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5935 -0.5723 0.1474 0.5911 2.8760
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.594024 0.77073
## team (Intercept) 0.001548 0.03935
## Residual 1.505408 1.22695
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.122927 0.212086 282.596992 24.155 <0.0000000000000002 ***
## highlowstatLow -1.527043 0.094449 1036.257973 -16.168 <0.0000000000000002 ***
## age 0.007266 0.005172 318.130700 1.405 0.1610
## gender_textNonBinary -0.158548 0.782891 398.362966 -0.203 0.8396
## gender_textWoman -0.062128 0.117837 322.133575 -0.527 0.5984
## monthssince -0.003509 0.004801 967.168658 -0.731 0.4650
## monthsjoined 0.006814 0.003350 949.904547 2.034 0.0422 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hghlwL age gnd_NB gndr_W mnthss
## highlwsttLw -0.204
## age -0.847 0.077
## gndr_txtNnB -0.065 -0.011 0.019
## gndr_txtWmn -0.220 -0.060 -0.120 0.082
## monthssince -0.007 -0.110 -0.016 -0.030 -0.013
## monthsjoind -0.218 0.052 -0.052 0.034 0.115 -0.418Mutability
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: hiermut ~ highlowstat + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3705.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3158 -0.5149 0.0344 0.5406 3.1557
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.8307 0.9114
## team (Intercept) 0.0000 0.0000
## Residual 1.1388 1.0671
## Number of obs: 1109, groups: pid, 334; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.62240 0.06634 457.82171 69.67 <0.0000000000000002 ***
## highlowstatLow -1.00583 0.08290 1072.07096 -12.13 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## highlwsttLw -0.446
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: hiermut ~ highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3491.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4043 -0.5083 0.0501 0.5246 3.3635
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.8404 0.9167
## team (Intercept) 0.0000 0.0000
## Residual 1.0987 1.0482
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.058161 0.220116 347.384368 22.980 <0.0000000000000002 ***
## highlowstatLow -1.048251 0.085085 999.353956 -12.320 <0.0000000000000002 ***
## age -0.008472 0.005452 314.003278 -1.554 0.1212
## gender_textNonBinary 0.111726 0.809524 366.367508 0.138 0.8903
## gender_textWoman -0.079992 0.124058 317.664902 -0.645 0.5195
## monthssince 0.005135 0.004438 1035.841270 1.157 0.2475
## monthsjoined -0.005907 0.003104 1032.242640 -1.903 0.0573 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hghlwL age gnd_NB gndr_W mnthss
## highlwsttLw -0.182
## age -0.862 0.066
## gndr_txtNnB -0.068 -0.010 0.021
## gndr_txtWmn -0.222 -0.049 -0.117 0.083
## monthssince -0.001 -0.122 -0.014 -0.027 -0.012
## monthsjoind -0.199 0.072 -0.043 0.029 0.101 -0.431
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Interactions
Continuous Status
DV: Voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice ~ hiermut * status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3204.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9737 -0.4588 0.0764 0.4869 3.0080
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.444928 0.6670
## team (Intercept) 0.004984 0.0706
## Residual 0.896766 0.9470
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.095742 0.291613 596.283266 3.758 0.000188 ***
## hiermut 0.259695 0.064555 1025.197972 4.023 0.0000617 ***
## status 0.618519 0.053832 1022.528830 11.490 < 0.0000000000000002 ***
## age 0.006520 0.004292 326.090620 1.519 0.129705
## gender_textNonBinary 0.736070 0.643834 395.410092 1.143 0.253622
## gender_textWoman -0.049533 0.097266 326.037634 -0.509 0.610921
## monthssince -0.004589 0.003833 998.052901 -1.197 0.231483
## monthsjoined 0.005692 0.002676 987.065893 2.127 0.033699 *
## hiermut:status -0.020692 0.012613 1030.551277 -1.641 0.101192
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt status age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.738
## status -0.676 0.710
## age -0.460 -0.005 -0.091
## gndr_txtNnB -0.083 0.032 0.074 0.010
## gndr_txtWmn -0.151 -0.007 0.008 -0.118 0.084
## monthssince -0.067 0.006 0.102 -0.026 -0.019 -0.013
## monthsjoind -0.120 0.037 -0.047 -0.040 0.027 0.110 -0.428
## hiermt:stts 0.684 -0.900 -0.890 0.042 -0.050 0.015 -0.038 0.000DV: Task Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futtask ~ hiermut * status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3758.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1831 -0.5671 -0.1091 0.5499 4.4372
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.793 0.8905
## team (Intercept) 0.000 0.0000
## Residual 1.519 1.2326
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.988551 0.379478 900.720679 15.781 < 0.0000000000000002 ***
## hiermut -0.366594 0.084327 1027.000190 -4.347 0.000015152 ***
## status -0.373337 0.070276 1021.433680 -5.312 0.000000133 ***
## age -0.008835 0.005674 327.766996 -1.557 0.120
## gender_textNonBinary -0.407895 0.849762 394.881079 -0.480 0.631
## gender_textWoman -0.067012 0.128586 327.734728 -0.521 0.603
## monthssince 0.003935 0.005015 1005.210283 0.785 0.433
## monthsjoined -0.002090 0.003498 996.377588 -0.598 0.550
## hiermut:status 0.026512 0.016472 1030.455558 1.609 0.108
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt status age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.741
## status -0.678 0.708
## age -0.469 -0.005 -0.090
## gndr_txtNnB -0.083 0.031 0.072 0.011
## gndr_txtWmn -0.153 -0.007 0.007 -0.118 0.083
## monthssince -0.068 0.008 0.105 -0.026 -0.018 -0.012
## monthsjoind -0.119 0.035 -0.050 -0.039 0.026 0.109 -0.428
## hiermt:stts 0.687 -0.900 -0.890 0.041 -0.049 0.015 -0.041 0.002
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')DV: Status Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futstatus ~ hiermut * status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3711
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.7312 -0.5487 -0.1143 0.5140 4.1433
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.140965 1.06816
## team (Intercept) 0.003965 0.06297
## Residual 1.300788 1.14052
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 5.640153 0.384559 834.849641 14.667 < 0.0000000000000002 ***
## hiermut -0.376714 0.081308 985.966972 -4.633 0.00000408 ***
## status -0.312431 0.067647 976.896251 -4.619 0.00000438 ***
## age -0.001734 0.006259 325.647512 -0.277 0.7819
## gender_textNonBinary -0.431179 0.924490 372.478533 -0.466 0.6412
## gender_textWoman -0.173660 0.141831 325.660182 -1.224 0.2217
## monthssince -0.002335 0.004936 1035.946050 -0.473 0.6362
## monthsjoined -0.002039 0.003453 1033.845083 -0.591 0.5549
## hiermut:status 0.033187 0.015912 994.132771 2.086 0.0373 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt status age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.700
## status -0.636 0.702
## age -0.526 -0.002 -0.079
## gndr_txtNnB -0.082 0.029 0.065 0.015
## gndr_txtWmn -0.159 -0.008 0.004 -0.116 0.084
## monthssince -0.069 0.012 0.110 -0.023 -0.017 -0.012
## monthsjoind -0.108 0.031 -0.057 -0.033 0.023 0.097 -0.439
## hiermt:stts 0.646 -0.896 -0.888 0.035 -0.045 0.015 -0.043 0.003DV: Prohibitive voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.proh ~ hiermut * status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3573.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5312 -0.4866 0.0438 0.5201 3.3252
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.9808832600649 0.99039551
## team (Intercept) 0.0000000002095 0.00001447
## Residual 1.1479679249279 1.07143265
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.4098550 0.3581974 870.1172045 3.936 0.000089473479406 ***
## hiermut 0.2329710 0.0762030 986.8128620 3.057 0.002294 **
## status 0.4665268 0.0633836 976.3035541 7.360 0.000000000000389 ***
## age 0.0008041 0.0058235 311.3266443 0.138 0.890268
## gender_textNonBinary -0.1433553 0.8607064 357.9353308 -0.167 0.867814
## gender_textWoman -0.4616575 0.1319735 311.3482693 -3.498 0.000537 ***
## monthssince -0.0031618 0.0046195 1035.9648247 -0.684 0.493850
## monthsjoined 0.0084512 0.0032285 1034.8094746 2.618 0.008981 **
## hiermut:status -0.0001108 0.0149078 994.4936207 -0.007 0.994069
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt status age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.705
## status -0.641 0.702
## age -0.524 -0.002 -0.080
## gndr_txtNnB -0.082 0.029 0.065 0.015
## gndr_txtWmn -0.159 -0.008 0.004 -0.116 0.084
## monthssince -0.069 0.013 0.111 -0.024 -0.017 -0.011
## monthsjoind -0.109 0.030 -0.058 -0.033 0.023 0.097 -0.438
## hiermt:stts 0.651 -0.896 -0.888 0.035 -0.045 0.015 -0.045 0.005
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')DV: Promotive voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.prom ~ hiermut * status + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3401.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9845 -0.5283 0.0901 0.5531 3.1843
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.420281 0.64829
## team (Intercept) 0.005154 0.07179
## Residual 1.143867 1.06952
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.24410432 0.31549292 751.66300789 3.943 0.0000879 ***
## hiermut 0.20310371 0.07113789 1034.57071117 2.855 0.00439 **
## status 0.57093790 0.05938207 1034.11692775 9.615 < 0.0000000000000002 ***
## age 0.00402055 0.00444751 320.61964183 0.904 0.36667
## gender_textNonBinary 0.59148472 0.67308308 402.53778901 0.879 0.38005
## gender_textWoman 0.00004913 0.10078781 320.56103867 0.000 0.99961
## monthssince 0.00050275 0.00417478 953.35055073 0.120 0.90417
## monthsjoined 0.00618413 0.00291191 940.94201504 2.124 0.03395 *
## hiermut:status -0.00670374 0.01388639 1035.41880355 -0.483 0.62937
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt status age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.755
## status -0.693 0.714
## age -0.433 -0.007 -0.097
## gndr_txtNnB -0.083 0.032 0.077 0.008
## gndr_txtWmn -0.149 -0.006 0.009 -0.120 0.083
## monthssince -0.066 0.004 0.098 -0.028 -0.019 -0.013
## monthsjoind -0.126 0.040 -0.043 -0.043 0.029 0.116 -0.422
## hiermt:stts 0.702 -0.902 -0.891 0.045 -0.052 0.015 -0.036 -0.001Binary Status
DV: Voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice ~ hiermut * highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3399.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.5966 -0.5219 0.0646 0.5416 2.5953
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.5278 0.7265
## team (Intercept) 0.0000 0.0000
## Residual 1.0961 1.0469
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.839537 0.266095 680.645412 14.429 < 0.0000000000000002 ***
## hiermut 0.264254 0.036660 1030.483901 7.208 0.00000000000109 ***
## highlowstatLow -1.596228 0.238373 998.414609 -6.696 0.00000000003561 ***
## age 0.011574 0.004690 323.586462 2.468 0.01412 *
## gender_textNonBinary 0.006387 0.705818 396.367843 0.009 0.99278
## gender_textWoman -0.077484 0.106549 325.436538 -0.727 0.46762
## monthssince -0.009930 0.004204 993.874537 -2.362 0.01838 *
## monthsjoined 0.008501 0.002935 987.339233 2.896 0.00386 **
## hiermut:highlowstatLow 0.076214 0.055804 994.566909 1.366 0.17233
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt hghlwL age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.699
## highlwsttLw -0.510 0.660
## age -0.662 0.076 0.085
## gndr_txtNnB -0.011 -0.052 -0.078 0.014
## gndr_txtWmn -0.176 0.026 -0.006 -0.117 0.081
## monthssince 0.042 -0.064 -0.095 -0.021 -0.024 -0.014
## monthsjoind -0.198 0.065 0.045 -0.045 0.030 0.112 -0.424
## hrmt:hghlwL 0.416 -0.596 -0.930 -0.057 0.079 -0.011 0.055 -0.017
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')DV: Task Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futtask ~ hiermut * highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3801.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.6730 -0.5925 -0.1288 0.5741 3.7897
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.8027 0.896
## team (Intercept) 0.0000 0.000
## Residual 1.6044 1.267
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.426447 0.324358 683.635065 13.647 < 0.0000000000000002 ***
## hiermut -0.297220 0.044528 1032.004821 -6.675 0.0000000000403 ***
## highlowstatLow 0.817165 0.289117 995.832505 2.826 0.0048 **
## age -0.012108 0.005741 326.441284 -2.109 0.0357 *
## gender_textNonBinary -0.021010 0.862938 397.828288 -0.024 0.9806
## gender_textWoman -0.046236 0.130412 328.295995 -0.355 0.7232
## monthssince 0.007528 0.005110 999.200434 1.473 0.1410
## monthsjoined -0.003837 0.003568 992.921035 -1.075 0.2825
## hiermut:highlowstatLow -0.077706 0.067679 991.896633 -1.148 0.2512
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt hghlwL age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.696
## highlwsttLw -0.508 0.659
## age -0.664 0.075 0.085
## gndr_txtNnB -0.011 -0.052 -0.077 0.015
## gndr_txtWmn -0.177 0.025 -0.005 -0.117 0.081
## monthssince 0.042 -0.065 -0.096 -0.021 -0.024 -0.014
## monthsjoind -0.198 0.064 0.045 -0.044 0.030 0.112 -0.424
## hrmt:hghlwL 0.415 -0.595 -0.930 -0.057 0.078 -0.011 0.056 -0.017
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')DV: Status Futility
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: futstatus ~ hiermut * highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3729
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9467 -0.5712 -0.0950 0.5399 3.9059
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.138236 1.06688
## team (Intercept) 0.003579 0.05983
## Residual 1.339848 1.15752
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 4.20800354 0.33418893 613.29698016 12.592 < 0.0000000000000002 ***
## hiermut -0.23693140 0.04293454 1027.21042937 -5.518 0.0000000433 ***
## highlowstatLow 0.79297004 0.27333450 943.62425049 2.901 0.0038 **
## age -0.00380421 0.00626584 324.03766478 -0.607 0.5442
## gender_textNonBinary -0.18276369 0.92801845 373.94026912 -0.197 0.8440
## gender_textWoman -0.16239874 0.14226128 325.75192504 -1.142 0.2545
## monthssince -0.00004078 0.00497580 1035.83204316 -0.008 0.9935
## monthsjoined -0.00329018 0.00348216 1033.35245340 -0.945 0.3449
## hiermut:highlowstatLow -0.10454110 0.06392418 938.32743115 -1.635 0.1023
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt hghlwL age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.650
## highlwsttLw -0.473 0.655
## age -0.693 0.067 0.074
## gndr_txtNnB -0.023 -0.044 -0.068 0.018
## gndr_txtWmn -0.182 0.022 -0.004 -0.115 0.082
## monthssince 0.040 -0.064 -0.104 -0.018 -0.022 -0.013
## monthsjoind -0.183 0.057 0.050 -0.038 0.028 0.099 -0.435
## hrmt:hghlwL 0.384 -0.590 -0.929 -0.049 0.069 -0.011 0.060 -0.019DV: Prohibitive voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.proh ~ hiermut * highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3682.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.02281 -0.54047 0.05573 0.54061 2.80338
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 1.065 1.032
## team (Intercept) 0.000 0.000
## Residual 1.291 1.136
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.359813 0.324148 654.684620 10.365 < 0.0000000000000002 ***
## hiermut 0.340425 0.042008 1028.891670 8.104 0.0000000000000015 ***
## highlowstatLow -1.169560 0.267571 941.526478 -4.371 0.0000137422962203 ***
## age 0.005283 0.006085 310.464452 0.868 0.38597
## gender_textNonBinary -0.783237 0.901858 360.295696 -0.868 0.38572
## gender_textWoman -0.488346 0.138163 312.162610 -3.535 0.00047 ***
## monthssince -0.007684 0.004865 1035.513871 -1.580 0.11451
## monthsjoined 0.010988 0.003401 1034.181298 3.230 0.00127 **
## hiermut:highlowstatLow 0.020012 0.062587 936.098353 0.320 0.74924
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt hghlwL age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.656
## highlwsttLw -0.476 0.655
## age -0.695 0.067 0.075
## gndr_txtNnB -0.023 -0.044 -0.068 0.018
## gndr_txtWmn -0.182 0.022 -0.004 -0.115 0.082
## monthssince 0.042 -0.065 -0.105 -0.019 -0.022 -0.013
## monthsjoind -0.186 0.058 0.052 -0.038 0.027 0.100 -0.434
## hrmt:hghlwL 0.387 -0.590 -0.929 -0.049 0.069 -0.011 0.062 -0.020
## optimizer (nloptwrap) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')DV: Promotive voice
## Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
## Formula: voice.prom ~ hiermut * highlowstat + age + gender_text + monthssince + monthsjoined + (1 | pid) + (1 | team)
## Data: teamrerun_clean_wide
##
## REML criterion at convergence: 3601.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3833 -0.5557 0.1260 0.5755 3.2128
##
## Random effects:
## Groups Name Variance Std.Dev.
## pid (Intercept) 0.521605 0.72222
## team (Intercept) 0.002521 0.05021
## Residual 1.390079 1.17902
## Number of obs: 1045, groups: pid, 322; team, 4
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 3.562835 0.287509 558.001374 12.392 < 0.0000000000000002 ***
## hiermut 0.307140 0.040262 1015.551450 7.628 0.0000000000000545 ***
## highlowstatLow -1.297958 0.264335 1015.146371 -4.910 0.0000010592795972 ***
## age 0.009725 0.004917 318.921687 1.978 0.04882 *
## gender_textNonBinary -0.184410 0.745694 402.484839 -0.247 0.80480
## gender_textWoman -0.035559 0.111723 320.759650 -0.318 0.75048
## monthssince -0.005287 0.004596 955.632555 -1.150 0.25034
## monthsjoined 0.009054 0.003209 945.465800 2.821 0.00488 **
## hiermut:highlowstatLow 0.027514 0.061897 1012.275191 0.445 0.65676
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) hiermt hghlwL age gnd_NB gndr_W mnthss mnthsj
## hiermut -0.712
## highlwsttLw -0.521 0.662
## age -0.646 0.079 0.090
## gndr_txtNnB -0.005 -0.056 -0.082 0.013
## gndr_txtWmn -0.173 0.027 -0.007 -0.118 0.081
## monthssince 0.039 -0.063 -0.090 -0.022 -0.025 -0.015
## monthsjoind -0.200 0.066 0.040 -0.048 0.032 0.117 -0.419
## hrmt:hghlwL 0.426 -0.599 -0.931 -0.061 0.083 -0.011 0.051 -0.014