Good man_MI_EG

Analysis 1: How accept vs. reject is affected by moral identity (MI) internalization:

## 
## Call:
## glm(formula = accept ~ moral_internalization, family = binomial, 
##     data = bad_reputation)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.4791  -1.4697   0.9087   0.9109   0.9242  
## 
## Coefficients:
##                       Estimate Std. Error z value Pr(>|z|)
## (Intercept)            0.73344    0.72283   1.015    0.310
## moral_internalization -0.01484    0.16191  -0.092    0.927
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 751.8  on 586  degrees of freedom
## Residual deviance: 751.8  on 585  degrees of freedom
##   (22 observations deleted due to missingness)
## AIC: 755.8
## 
## Number of Fisher Scoring iterations: 4

Analysis 1.1: How accept vs. reject is affected by the interaction between MI internalization and fair, unfair offers:

## 
## Call:
## glm(formula = accept ~ moral_internalization * (fair + selfish), 
##     family = binomial, data = bad_reputation)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -3.0646  -0.9227   0.1355   0.9306   1.4955  
## 
## Coefficients:
##                               Estimate Std. Error z value Pr(>|z|)
## (Intercept)                    0.98027    1.23137   0.796    0.426
## moral_internalization         -0.08354    0.27561  -0.303    0.762
## fair                           7.04375    5.10496   1.380    0.168
## selfish                       -1.79140    1.74386  -1.027    0.304
## moral_internalization:fair    -0.67495    1.08047  -0.625    0.532
## moral_internalization:selfish  0.12387    0.39047   0.317    0.751
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 751.80  on 586  degrees of freedom
## Residual deviance: 529.09  on 581  degrees of freedom
##   (22 observations deleted due to missingness)
## AIC: 541.09
## 
## Number of Fisher Scoring iterations: 7

Analysis 2: How accept vs. reject is affected MI symbolization:

## 
## Call:
## glm(formula = accept ~ moral_symbolization, family = binomial, 
##     data = bad_reputation)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.5477  -1.4511   0.8960   0.9187   0.9615  
## 
## Coefficients:
##                     Estimate Std. Error z value Pr(>|z|)   
## (Intercept)          0.88942    0.30402   2.926  0.00344 **
## moral_symbolization -0.05109    0.06688  -0.764  0.44495   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 751.80  on 586  degrees of freedom
## Residual deviance: 751.22  on 585  degrees of freedom
##   (22 observations deleted due to missingness)
## AIC: 755.22
## 
## Number of Fisher Scoring iterations: 4

Analysis 2.1: How accept vs. reject is affected by the interaction between MI symbolization and fair, unfair offers:

## 
## Call:
## glm(formula = accept ~ moral_symbolization * (fair + selfish), 
##     family = binomial, data = bad_reputation)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -3.0505  -0.8950   0.1417   0.9307   1.5943  
## 
## Coefficients:
##                             Estimate Std. Error z value Pr(>|z|)
## (Intercept)                  0.69327    0.51405   1.349    0.177
## moral_symbolization         -0.01924    0.11359  -0.169    0.866
## fair                         3.53781    2.39847   1.475    0.140
## selfish                     -0.70055    0.72010  -0.973    0.331
## moral_symbolization:fair     0.09851    0.54331   0.181    0.856
## moral_symbolization:selfish -0.12675    0.16042  -0.790    0.429
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 751.80  on 586  degrees of freedom
## Residual deviance: 527.92  on 581  degrees of freedom
##   (22 observations deleted due to missingness)
## AIC: 539.92
## 
## Number of Fisher Scoring iterations: 7