25_11.24-OpenEndedVign

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Demographic information

Raw

Age

Gender

## gender_text
## Non-binary/Other            Woman 
##                1              279

Race

## racef
##                      White Traditionally Marginalized                Multiracial                      Asian 
##                        193                         35                         25                         16
## racef
##                      White Traditionally Marginalized                Multiracial                      Asian 
##                   0.681979                   0.123675                   0.088339                   0.056537

Failed attention check

## filterout
## Exclude  Retain 
##      36     244

Clean

Age

vignsexismclean %>% ungroup() %>% dplyr::summarize(mean_age = mean(age, na.rm = TRUE), sd_age = sd(age, na.rm = TRUE))

Gender

## gender_text
## Woman 
##   243

Race

## racef
##                      White Traditionally Marginalized                Multiracial                      Asian 
##                        170                         29                         19                         14
## racef
##                      White Traditionally Marginalized                Multiracial                      Asian 
##                   0.699588                   0.119342                   0.078189                   0.057613

Alphas

Need for significance

Status

Rewards

## 
##  Pearson's product-moment correlation
## 
## data:  reward1 and reward2
## t = 16.6, df = 241, p-value <0.0000000000000002
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.66635 0.78458
## sample estimates:
##     cor 
## 0.73091

Social Rewards

Means + SDs

Analyses

Main effects

Binary

Reprimanded

## 
## Call:
## glm(formula = reprimanded ~ instigation_type_rev, family = "binomial", 
##     data = vignsexismclean)
## 
## Coefficients:
##                               Estimate Std. Error z value   Pr(>|z|)    
## (Intercept)                      0.164      0.182    0.90       0.37    
## instigation_type_revprejudice   -1.725      0.301   -5.73 0.00000001 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 317.00  on 242  degrees of freedom
## Residual deviance: 279.98  on 241  degrees of freedom
## AIC: 284
## 
## Number of Fisher Scoring iterations: 3

Jeff uncivil

## 
## Call:
## glm(formula = jeffuncivil ~ instigation_type_rev, family = "binomial", 
##     data = vignsexismclean)
## 
## Coefficients:
##                               Estimate Std. Error z value      Pr(>|z|)    
## (Intercept)                      0.197      0.182    1.08          0.28    
## instigation_type_revprejudice   -2.079      0.324   -6.41 0.00000000014 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 312.04  on 242  degrees of freedom
## Residual deviance: 262.47  on 241  degrees of freedom
## AIC: 266.5
## 
## Number of Fisher Scoring iterations: 4

Paul uncivil

## 
## Call:
## glm(formula = pauluncivil ~ instigation_type_rev, family = "binomial", 
##     data = vignsexismclean)
## 
## Coefficients:
##                               Estimate Std. Error z value Pr(>|z|)    
## (Intercept)                      0.433      0.185    2.34     0.02 *  
## instigation_type_revprejudice    1.248      0.311    4.01 0.000061 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 286.19  on 242  degrees of freedom
## Residual deviance: 268.74  on 241  degrees of freedom
## AIC: 272.7
## 
## Number of Fisher Scoring iterations: 4

Mediation

Midpoint analyses

Tables

Means/SDs/Correlations

Means/SDs

Correlations

Main effects

Midpoints

Controls

Likert

  nfs nfs status status rewards rewards socreward socreward
Predictors B SE T-value df B SE T-value df B SE T-value df B SE T-value df B SE T-value df B SE T-value df B SE T-value df B SE T-value df
(Intercept) 4.16 *** 0.14 28.77 241.00 3.43 *** 0.67 5.12 221.00 0.57 *** 0.14 4.14 241.00 0.98 0.60 1.64 221.00 0.09 0.12 0.74 241.00 0.29 0.54 0.53 221.00 0.34 * 0.14 2.44 241.00 0.48 0.64 0.74 221.00
age -0.00 0.01 -0.42 221.00 -0.01 * 0.01 -2.01 221.00 -0.01 0.01 -1.78 221.00 -0.01 0.01 -1.71 221.00
prejudice Reference Reference Reference Reference Reference Reference Reference Reference
traditional -1.15 *** 0.20 -5.64 241.00 -0.67 ** 0.21 -3.24 221.00 -1.14 *** 0.19 -5.89 241.00 -0.56 ** 0.19 -3.02 221.00 -0.57 *** 0.17 -3.45 241.00 -0.20 0.17 -1.18 221.00 -1.08 *** 0.20 -5.41 241.00 -0.59 ** 0.20 -2.94 221.00
learn1 -0.02 0.07 -0.30 221.00 0.03 0.06 0.54 221.00 0.08 0.05 1.48 221.00 0.07 0.06 1.11 221.00
learn2 -0.01 0.08 -0.09 221.00 -0.16 * 0.07 -2.37 221.00 -0.14 * 0.06 -2.31 221.00 -0.17 * 0.07 -2.25 221.00
learn3 0.27 ** 0.09 3.17 221.00 0.21 ** 0.08 2.68 221.00 0.20 ** 0.07 2.80 221.00 0.26 ** 0.08 3.15 221.00
White Reference Reference Reference Reference Reference Reference Reference Reference
Traditionally
Marginalized 		0.25 0.30 0.82 221.00 0.25 0.27 0.91 221.00 0.15 0.25 0.63 221.00 0.06 0.29 0.21 221.00
Multiracial 0.10 0.36 0.28 221.00 0.10 0.32 0.32 221.00 0.26 0.29 0.90 221.00 0.25 0.35 0.72 221.00
Asian 0.22 0.41 0.53 221.00 0.43 0.37 1.18 221.00 0.31 0.34 0.94 221.00 0.23 0.40 0.58 221.00
rudeness1 -0.20 * 0.09 -2.12 221.00 -0.19 * 0.08 -2.32 221.00 -0.06 0.07 -0.79 221.00 -0.11 0.09 -1.26 221.00
rudeness2 0.35 *** 0.07 5.30 221.00 0.48 *** 0.06 8.11 221.00 0.32 *** 0.05 5.91 221.00 0.39 *** 0.06 6.08 221.00
Observations 243 232 243 232 243 232 243 232
R2 / R2 adjusted 0.117 / 0.113 0.304 / 0.273 0.126 / 0.122 0.398 / 0.371 0.047 / 0.043 0.253 / 0.219 0.108 / 0.105 0.305 / 0.274
  • p<0.05   ** p<0.01   *** p<0.001

Binary

  reprimanded reprimanded jeffuncivil jeffuncivil pauluncivil pauluncivil
Predictors B SE T-value df B SE T-value df B SE T-value df B SE T-value df B SE T-value df B SE T-value df
(Intercept) 0.21 *** 0.05 -6.50 Inf 0.33 0.38 -0.96 Inf 0.15 *** 0.04 -7.01 Inf 0.05 * 0.06 -2.45 Inf 5.37 *** 1.34 6.73 Inf 0.22 0.26 -1.26 Inf
age 1.00 0.01 0.21 Inf 1.00 0.02 0.33 Inf 0.98 0.01 -1.23 Inf
prejudice Reference Reference Reference Reference Reference Reference
traditional 5.61 *** 1.69 5.73 Inf 3.00 ** 1.07 3.06 Inf 7.99 *** 2.59 6.41 Inf 5.04 *** 1.91 4.27 Inf 0.29 *** 0.09 -4.01 Inf 0.29 ** 0.11 -3.28 Inf
learn1 0.93 0.11 -0.64 Inf 1.19 0.15 1.38 Inf 1.47 ** 0.19 3.06 Inf
learn2 1.30 0.18 1.94 Inf 1.36 * 0.19 2.18 Inf 1.24 0.17 1.50 Inf
learn3 0.80 0.12 -1.48 Inf 0.69 * 0.11 -2.37 Inf 0.96 0.15 -0.25 Inf
White Reference Reference Reference Reference Reference Reference
Traditionally
Marginalized 		0.77 0.42 -0.48 Inf 0.91 0.52 -0.17 Inf 1.12 0.59 0.22 Inf
Multiracial 0.18 * 0.15 -2.13 Inf 0.43 0.31 -1.16 Inf 0.55 0.33 -1.00 Inf
Asian 0.70 0.53 -0.47 Inf 0.64 0.54 -0.54 Inf 0.42 0.30 -1.23 Inf
rudeness1 1.68 ** 0.31 2.85 Inf 1.30 0.22 1.56 Inf 0.49 *** 0.08 -4.35 Inf
rudeness2 0.52 *** 0.08 -4.42 Inf 0.57 *** 0.08 -3.87 Inf 0.87 0.10 -1.22 Inf
Observations 243 232 243 232 243 232
R2 Tjur 0.147 0.320 0.193 0.350 0.070 0.255
  • p<0.05   ** p<0.01   *** p<0.001