Main Effects
Incivility
Gender
Interactions
Incivility condition on supervisor gender
We do not find any significant interactions between incivility and supervisor gender, except for on incivility.
Incivility ~ Condition * Supervisor Gender
Combining all of the supervisor genders and moderators
Gender of uncivil actor as independent variable
##
## Call:
## lm(formula = statusc ~ morallygood * Sup_Gender + Condition,
## data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.918 -0.334 -0.178 0.562 2.813
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.2229 0.1554 -1.43 0.152
## morallygood 0.7521 0.0445 16.90 <0.0000000000000002 ***
## Sup_GenderWoman -0.2352 0.2152 -1.09 0.275
## ConditionUncivil -0.1030 0.1119 -0.92 0.358
## morallygood:Sup_GenderWoman 0.1437 0.0611 2.35 0.019 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.95 on 311 degrees of freedom
## Multiple R-squared: 0.699, Adjusted R-squared: 0.695
## F-statistic: 181 on 4 and 311 DF, p-value: <0.0000000000000002## SIMPLE SLOPES ANALYSIS
##
## Slope of morallygood when Sup_Gender = Woman:
##
## Est. S.E. t val. p
## ------ ------ -------- ------
## 0.90 0.04 20.39 0.00
##
## Slope of morallygood when Sup_Gender = Man:
##
## Est. S.E. t val. p
## ------ ------ -------- ------
## 0.75 0.04 16.90 0.00
Three way interactions between supervisor gender and incivility and civility
##
## Call:
## lm(formula = fnvpre ~ civility * Sup_Gender * Condition, data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.553 -0.675 -0.253 0.426 3.113
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.004676 0.295469 6.78 0.00000000006 ***
## civility -0.041990 0.067387 -0.62 0.53
## Sup_GenderWoman 0.103607 0.432967 0.24 0.81
## ConditionUncivil 0.761025 0.567751 1.34 0.18
## civility:Sup_GenderWoman 0.000513 0.102733 0.00 1.00
## civility:ConditionUncivil -0.033008 0.114826 -0.29 0.77
## Sup_GenderWoman:ConditionUncivil 0.225464 0.886539 0.25 0.80
## civility:Sup_GenderWoman:ConditionUncivil -0.059362 0.175942 -0.34 0.74
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.96 on 308 degrees of freedom
## Multiple R-squared: 0.0713, Adjusted R-squared: 0.0502
## F-statistic: 3.38 on 7 and 308 DF, p-value: 0.00172##
## Call:
## lm(formula = fnvpro ~ civility * Sup_Gender * Condition, data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3070 -0.8295 0.0271 0.7795 2.3821
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3202 0.3461 9.59 <0.0000000000000002 ***
## civility -0.0132 0.0789 -0.17 0.867
## Sup_GenderWoman -0.4212 0.5071 -0.83 0.407
## ConditionUncivil -1.5182 0.6650 -2.28 0.023 *
## civility:Sup_GenderWoman 0.0451 0.1203 0.38 0.708
## civility:ConditionUncivil 0.1657 0.1345 1.23 0.219
## Sup_GenderWoman:ConditionUncivil 1.2295 1.0383 1.18 0.237
## civility:Sup_GenderWoman:ConditionUncivil -0.1943 0.2061 -0.94 0.347
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.1 on 308 degrees of freedom
## Multiple R-squared: 0.0689, Adjusted R-squared: 0.0477
## F-statistic: 3.26 on 7 and 308 DF, p-value: 0.00238##
## Call:
## lm(formula = protect ~ civility * Sup_Gender * Condition, data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.220 -1.026 -0.776 0.986 5.154
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.7433 0.5394 3.23 0.0014 **
## civility 0.0176 0.1230 0.14 0.8861
## Sup_GenderWoman 0.0432 0.7904 0.05 0.9565
## ConditionUncivil 1.9032 1.0365 1.84 0.0673 .
## civility:Sup_GenderWoman 0.0416 0.1875 0.22 0.8246
## civility:ConditionUncivil -0.1199 0.2096 -0.57 0.5679
## Sup_GenderWoman:ConditionUncivil 1.3291 1.6185 0.82 0.4121
## civility:Sup_GenderWoman:ConditionUncivil -0.2815 0.3212 -0.88 0.3815
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.8 on 308 degrees of freedom
## Multiple R-squared: 0.122, Adjusted R-squared: 0.102
## F-statistic: 6.14 on 7 and 308 DF, p-value: 0.000000995##
## Call:
## lm(formula = warmth ~ civility * Sup_Gender * Condition, data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.515 -0.805 -0.311 0.461 3.297
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.754075 0.337677 5.19 0.00000037 ***
## civility 0.011190 0.077013 0.15 0.88
## Sup_GenderWoman 0.543770 0.494815 1.10 0.27
## ConditionUncivil 0.495930 0.648852 0.76 0.45
## civility:Sup_GenderWoman -0.113092 0.117408 -0.96 0.34
## civility:ConditionUncivil -0.000618 0.131228 0.00 1.00
## Sup_GenderWoman:ConditionUncivil -0.157730 1.013179 -0.16 0.88
## civility:Sup_GenderWoman:ConditionUncivil 0.050825 0.201075 0.25 0.80
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.1 on 308 degrees of freedom
## Multiple R-squared: 0.0527, Adjusted R-squared: 0.0311
## F-statistic: 2.45 on 7 and 308 DF, p-value: 0.0188##
## Call:
## lm(formula = competence ~ civility * Sup_Gender * Condition,
## data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.873 -0.826 -0.260 0.657 3.154
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.09626 0.32933 6.37 0.00000000071 ***
## civility -0.04997 0.07511 -0.67 0.51
## Sup_GenderWoman 0.32248 0.48258 0.67 0.50
## ConditionUncivil 0.48070 0.63281 0.76 0.45
## civility:Sup_GenderWoman -0.03194 0.11451 -0.28 0.78
## civility:ConditionUncivil -0.00821 0.12798 -0.06 0.95
## Sup_GenderWoman:ConditionUncivil 0.37889 0.98813 0.38 0.70
## civility:Sup_GenderWoman:ConditionUncivil -0.08368 0.19610 -0.43 0.67
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.1 on 308 degrees of freedom
## Multiple R-squared: 0.0382, Adjusted R-squared: 0.0163
## F-statistic: 1.75 on 7 and 308 DF, p-value: 0.0978##
## Call:
## lm(formula = virtad ~ civility * Sup_Gender * Condition, data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.048 -1.008 -0.606 0.574 5.125
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.87526234 0.51866652 3.62 0.00035 ***
## civility 0.00000774 0.11829141 0.00 0.99995
## Sup_GenderWoman 0.37507851 0.76002859 0.49 0.62201
## ConditionUncivil 1.74655631 0.99662826 1.75 0.08069 .
## civility:Sup_GenderWoman -0.05236042 0.18033729 -0.29 0.77175
## civility:ConditionUncivil -0.16277270 0.20156476 -0.81 0.41998
## Sup_GenderWoman:ConditionUncivil 0.97525327 1.55622841 0.63 0.53133
## civility:Sup_GenderWoman:ConditionUncivil -0.18107824 0.30884819 -0.59 0.55810
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.7 on 308 degrees of freedom
## Multiple R-squared: 0.0769, Adjusted R-squared: 0.056
## F-statistic: 3.67 on 7 and 308 DF, p-value: 0.000804##
## Call:
## lm(formula = statusc ~ civility * Sup_Gender * Condition, data = transcript1clean)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.540 -0.840 -0.711 0.444 5.166
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.4735 0.5187 2.84 0.0048 **
## civility 0.0509 0.1183 0.43 0.6675
## Sup_GenderWoman 0.3593 0.7601 0.47 0.6368
## ConditionUncivil 0.9508 0.9968 0.95 0.3409
## civility:Sup_GenderWoman -0.0496 0.1804 -0.27 0.7835
## civility:ConditionUncivil -0.0388 0.2016 -0.19 0.8476
## Sup_GenderWoman:ConditionUncivil 1.5074 1.5565 0.97 0.3336
## civility:Sup_GenderWoman:ConditionUncivil -0.2842 0.3089 -0.92 0.3583
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.7 on 308 degrees of freedom
## Multiple R-squared: 0.0588, Adjusted R-squared: 0.0374
## F-statistic: 2.75 on 7 and 308 DF, p-value: 0.00877