##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## PROCESS is now ready for use.
## Copyright 2022 by Andrew F. Hayes ALL RIGHTS RESERVED
## Workshop schedule at http://haskayne.ucalgary.ca/CCRAM
## ##
## Call:
## lm(formula = punishment ~ ses_origin_, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.5984 -0.5984 0.0082 1.0082 2.6149
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.38508 0.11576 29.242 < 2e-16 ***
## ses_origin_ 0.60667 0.08947 6.781 5.93e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.3 on 314 degrees of freedom
## Multiple R-squared: 0.1277, Adjusted R-squared: 0.125
## F-statistic: 45.98 on 1 and 314 DF, p-value: 5.933e-11Mediation analysis: ses_origin_ -> surprise -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : surprise
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: surprise
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4263 0.1818 2.9768 34.7673 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.3524 0.1684 13.9709 0.0000 2.0211 2.6837
## X1 1.8952 0.2381 7.9591 0.0000 1.4267 2.3638
## X2 1.4589 0.2376 6.1414 0.0000 0.9915 1.9264
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4479 0.2007 1.5577 26.1060 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8099 0.1552 18.1052 0.0000 2.5045 3.1152
## X1 0.5214 0.1889 2.7605 0.0061 0.1498 0.8930
## X2 0.9192 0.1819 5.0531 0.0000 0.5613 1.2771
## surprise 0.2023 0.0409 4.9473 0.0000 0.1218 0.2827
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5214 0.1889 2.7605 0.0061 0.1498 0.8930
## X2 0.9192 0.1819 5.0531 0.0000 0.5613 1.2771
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0655 12.7744 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3834 0.0956 0.2092 0.5855
## X2 0.2951 0.0836 0.1481 0.4759
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3834 0.0918 4.1780 0.0000
## X2 0.2951 0.0772 3.8221 0.0001
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> sympathy -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : sympathy
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6456 0.4169 2.2599 111.8762 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.1905 0.1467 28.5639 0.0000 3.9018 4.4791
## X1 -2.0381 0.2075 -9.8234 0.0000 -2.4463 -1.6299
## X2 -3.0395 0.2070 -14.6849 0.0000 -3.4468 -2.6323
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5106 0.2607 1.4407 36.6732 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.6469 0.2225 20.8892 0.0000 4.2092 5.0846
## X1 0.2427 0.1895 1.2811 0.2011 -0.1301 0.6155
## X2 0.2270 0.2148 1.0568 0.2914 -0.1956 0.6496
## sympathy -0.3248 0.0451 -7.1975 0.0000 -0.4136 -0.2360
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.2427 0.1895 1.2811 0.2011 -0.1301 0.6155
## X2 0.2270 0.2148 1.0568 0.2914 -0.1956 0.6496
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0041 0.8652 2.0000 312.0000 0.4220
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> sympathy -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.6620 0.1235 0.4403 0.9197
## X2 0.9873 0.1560 0.6909 1.2968
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.6620 0.1144 5.7864 0.0000
## X2 0.9873 0.1531 6.4509 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> character -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : character
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: character
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3237 0.1048 1.2312 18.3180 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0095 0.1083 27.7927 0.0000 2.7965 3.2226
## X1 -0.4762 0.1531 -3.1096 0.0020 -0.7775 -0.1749
## X2 -0.9246 0.1528 -6.0521 0.0000 -1.2252 -0.6240
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4589 0.2106 1.5383 27.7421 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.3045 0.2254 19.0969 0.0000 3.8610 4.7480
## X1 0.7436 0.1738 4.2782 0.0000 0.4016 1.0855
## X2 0.9013 0.1805 4.9936 0.0000 0.5462 1.2564
## character -0.3385 0.0632 -5.3579 0.0000 -0.4628 -0.2142
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7436 0.1738 4.2782 0.0000 0.4016 1.0855
## X2 0.9013 0.1805 4.9936 0.0000 0.5462 1.2564
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0728 14.3789 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> character -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1612 0.0636 0.0550 0.3012
## X2 0.3130 0.0915 0.1498 0.5066
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1612 0.0607 2.6551 0.0079
## X2 0.3130 0.0786 3.9813 0.0001
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> wrongness -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : wrongness
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: wrongness
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2315 0.0536 1.5435 8.8612 2.0000 313.0000 0.0002
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.6762 0.1212 38.5688 0.0000 4.4376 4.9147
## X1 0.3714 0.1715 2.1662 0.0310 0.0341 0.7088
## X2 0.7200 0.1711 4.2093 0.0000 0.3835 1.0566
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5748 0.3304 1.3048 51.3178 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.9843 0.2674 3.6816 0.0003 0.4583 1.5104
## X1 0.7220 0.1588 4.5456 0.0000 0.4095 1.0345
## X2 0.8599 0.1617 5.3190 0.0000 0.5418 1.1780
## wrongness 0.4921 0.0520 9.4698 0.0000 0.3899 0.5944
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7220 0.1588 4.5456 0.0000 0.4095 1.0345
## X2 0.8599 0.1617 5.3190 0.0000 0.5418 1.1780
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0704 16.3952 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> wrongness -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1828 0.0989 0.0043 0.3889
## X2 0.3544 0.0994 0.1777 0.5653
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1828 0.0870 2.1006 0.0357
## X2 0.3544 0.0926 3.8286 0.0001
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> justification -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : justification
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: justification
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2967 0.0880 2.1492 15.1025 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.4762 0.1431 10.3182 0.0000 1.1947 1.7577
## X1 -0.5143 0.2023 -2.5418 0.0115 -0.9124 -0.1162
## X2 -1.1083 0.2018 -5.4905 0.0000 -1.5054 -0.7111
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4478 0.2006 1.5579 26.0905 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6369 0.1410 25.7920 0.0000 3.3594 3.9143
## X1 0.7824 0.1740 4.4959 0.0000 0.4400 1.1248
## X2 0.9506 0.1799 5.2832 0.0000 0.5966 1.3047
## justification -0.2379 0.0481 -4.9433 0.0000 -0.3326 -0.1432
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7824 0.1740 4.4959 0.0000 0.4400 1.1248
## X2 0.9506 0.1799 5.2832 0.0000 0.5966 1.3047
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0825 16.0908 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justification -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1223 0.0707 0.0134 0.2893
## X2 0.2636 0.0793 0.1270 0.4373
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1223 0.0550 2.2248 0.0261
## X2 0.2636 0.0724 3.6405 0.0003
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> reasons -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : reasons
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: reasons
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3564 0.1270 2.4053 22.7730 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.9429 0.1514 12.8366 0.0000 1.6451 2.2407
## X1 -1.0381 0.2140 -4.8499 0.0000 -1.4592 -0.6169
## X2 -1.3863 0.2135 -6.4918 0.0000 -1.8064 -0.9661
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4858 0.2360 1.4887 32.1296 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8325 0.1471 26.0511 0.0000 3.5430 4.1220
## X1 0.6126 0.1746 3.5085 0.0005 0.2690 0.9562
## X2 0.8241 0.1790 4.6055 0.0000 0.4720 1.1763
## reasons -0.2814 0.0445 -6.3288 0.0000 -0.3689 -0.1939
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6126 0.1746 3.5085 0.0005 0.2690 0.9562
## X2 0.8241 0.1790 4.6055 0.0000 0.4720 1.1763
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0554 11.3151 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> reasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2922 0.0880 0.1425 0.4854
## X2 0.3901 0.0924 0.2256 0.5888
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2922 0.0765 3.8196 0.0001
## X2 0.3901 0.0866 4.5043 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> justreasons -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : justreasons
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: justreasons
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3505 0.1228 1.9082 21.9126 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.7095 0.1348 12.6811 0.0000 1.4443 1.9748
## X1 -0.7762 0.1906 -4.0713 0.0001 -1.1513 -0.4011
## X2 -1.2473 0.1902 -6.5577 0.0000 -1.6215 -0.8730
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4829 0.2332 1.4943 31.6226 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8180 0.1468 26.0121 0.0000 3.5292 4.1067
## X1 0.6631 0.1731 3.8303 0.0002 0.3225 1.0037
## X2 0.8260 0.1795 4.6015 0.0000 0.4728 1.1792
## justreasons -0.3113 0.0500 -6.2244 0.0000 -0.4098 -0.2129
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6631 0.1731 3.8303 0.0002 0.3225 1.0037
## X2 0.8260 0.1795 4.6015 0.0000 0.4728 1.1792
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0585 11.8924 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justreasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2417 0.0837 0.0975 0.4299
## X2 0.3883 0.0889 0.2271 0.5794
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2417 0.0716 3.3768 0.0007
## X2 0.3883 0.0865 4.4872 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> guilt -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : guilt
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: guilt
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2633 0.0693 1.9793 11.6589 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.4667 0.1373 25.2492 0.0000 3.1965 3.7368
## X1 -0.5619 0.1942 -2.8939 0.0041 -0.9439 -0.1799
## X2 -0.9289 0.1937 -4.7955 0.0000 -1.3101 -0.5478
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4027 0.1622 1.6326 20.1355 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8206 0.2173 17.5826 0.0000 3.3931 4.2482
## X1 0.8181 0.1787 4.5782 0.0000 0.4665 1.1696
## X2 1.0709 0.1823 5.8755 0.0000 0.7123 1.4296
## guilt -0.1543 0.0513 -3.0058 0.0029 -0.2553 -0.0533
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8181 0.1787 4.5782 0.0000 0.4665 1.1696
## X2 1.0709 0.1823 5.8755 0.0000 0.7123 1.4296
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1013 18.8538 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> guilt -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0867 0.0459 0.0141 0.1906
## X2 0.1433 0.0630 0.0322 0.2804
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0867 0.0428 2.0273 0.0426
## X2 0.1433 0.0572 2.5080 0.0121
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> emo_sup -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : emo_sup
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: emo_sup
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3661 0.1340 1.7914 24.2241 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.6381 0.1306 20.1972 0.0000 2.3811 2.8951
## X1 1.2857 0.1847 6.9603 0.0000 0.9223 1.6492
## X2 0.6355 0.1843 3.4484 0.0006 0.2729 0.9981
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3720 0.1384 1.6790 16.7022 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.3427 0.1919 17.4178 0.0000 2.9651 3.7203
## X1 0.9326 0.1922 4.8526 0.0000 0.5544 1.3107
## X2 1.2280 0.1818 6.7559 0.0000 0.8704 1.5857
## emo_sup -0.0216 0.0547 -0.3950 0.6931 -0.1293 0.0861
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9326 0.1922 4.8526 0.0000 0.5544 1.3107
## X2 1.2280 0.1818 6.7559 0.0000 0.8704 1.5857
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1324 23.9689 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> emo_sup -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0278 0.0709 -0.1731 0.1051
## X2 -0.0137 0.0367 -0.0955 0.0516
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0278 0.0712 -0.3903 0.6963
## X2 -0.0137 0.0364 -0.3771 0.7061
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> abuse -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : abuse
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: abuse
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3512 0.1234 2.1275 22.0249 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.4857 0.1423 24.4878 0.0000 3.2056 3.7658
## X1 -1.3333 0.2013 -6.6234 0.0000 -1.7294 -0.9372
## X2 -0.7404 0.2008 -3.6868 0.0003 -1.1356 -0.3453
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3721 0.1384 1.6789 16.7108 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.3596 0.2159 15.5593 0.0000 2.9348 3.7845
## X1 0.8765 0.1909 4.5902 0.0000 0.5008 1.2522
## X2 1.1986 0.1822 6.5770 0.0000 0.8400 1.5572
## abuse -0.0212 0.0502 -0.4223 0.6731 -0.1200 0.0776
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8765 0.1909 4.5902 0.0000 0.5008 1.2522
## X2 1.1986 0.1822 6.5770 0.0000 0.8400 1.5572
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1241 22.4677 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> abuse -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0283 0.0691 -0.1008 0.1723
## X2 0.0157 0.0390 -0.0623 0.0955
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0283 0.0678 0.4167 0.6769
## X2 0.0157 0.0388 0.4051 0.6854
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> SFC -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : SFC
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: SFC
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1856 0.0345 1.8593 5.5849 2.0000 313.0000 0.0041
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6095 0.1331 27.1247 0.0000 3.3477 3.8714
## X1 0.5143 0.1882 2.7328 0.0066 0.1440 0.8846
## X2 0.5697 0.1877 3.0345 0.0026 0.2003 0.9391
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5087 0.2587 1.4445 36.3011 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.0035 0.2147 9.3317 0.0000 1.5810 2.4259
## X1 0.7221 0.1678 4.3021 0.0000 0.3918 1.0523
## X2 1.0119 0.1679 6.0269 0.0000 0.6815 1.3423
## SFC 0.3552 0.0498 7.1304 0.0000 0.2572 0.4533
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7221 0.1678 4.3021 0.0000 0.3918 1.0523
## X2 1.0119 0.1679 6.0269 0.0000 0.6815 1.3423
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0910 19.1473 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SFC -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1827 0.0764 0.0499 0.3478
## X2 0.2024 0.0809 0.0595 0.3725
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1827 0.0722 2.5302 0.0114
## X2 0.2024 0.0731 2.7692 0.0056
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> SE -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : SE
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2811 0.0790 1.6829 13.4253 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.9143 0.1266 23.0195 0.0000 2.6652 3.1634
## X1 0.4476 0.1790 2.5001 0.0129 0.0953 0.7999
## X2 0.9253 0.1786 5.1806 0.0000 0.5739 1.2768
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5261 0.2767 1.4094 39.7936 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.1193 0.1901 11.1467 0.0000 1.7452 2.4934
## X1 0.7256 0.1655 4.3850 0.0000 0.4000 1.0512
## X2 0.8439 0.1703 4.9548 0.0000 0.5088 1.1790
## SE 0.4003 0.0517 7.7378 0.0000 0.2985 0.5020
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7256 0.1655 4.3850 0.0000 0.4000 1.0512
## X2 0.8439 0.1703 4.9548 0.0000 0.5088 1.1790
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0675 14.5567 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SE -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1792 0.0803 0.0341 0.3469
## X2 0.3704 0.0909 0.2087 0.5626
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1792 0.0759 2.3612 0.0182
## X2 0.3704 0.0865 4.2802 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> upbringing -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M : upbringing
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: upbringing
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3373 0.1138 1.9615 20.0875 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.2000 0.1367 30.7293 0.0000 3.9311 4.4689
## X1 -1.2000 0.1933 -6.2083 0.0000 -1.5803 -0.8197
## X2 -0.8132 0.1928 -4.2171 0.0000 -1.1926 -0.4338
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3824 0.1462 1.6638 17.8079 3.0000 312.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6654 0.2523 14.5285 0.0000 3.1690 4.1618
## X1 0.7963 0.1887 4.2207 0.0000 0.4251 1.1675
## X2 1.1408 0.1826 6.2482 0.0000 0.7815 1.5000
## upbringing -0.0904 0.0521 -1.7365 0.0835 -0.1928 0.0120
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7963 0.1887 4.2207 0.0000 0.4251 1.1675
## X2 1.1408 0.1826 6.2482 0.0000 0.7815 1.5000
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1097 20.0476 2.0000 312.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> upbringing -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1085 0.0635 -0.0067 0.2428
## X2 0.0735 0.0441 -0.0042 0.1703
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1085 0.0656 1.6526 0.0984
## X2 0.0735 0.0469 1.5685 0.1168
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediators in parallel:
(not emo_sup, abuse, upbringing)
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : ses_origin_
## M1 : surprise
## M2 : sympathy
## M3 : character
## M4 : wrongness
## M5 : justreasons
## M6 : guilt
## M7 : SFC
## M8 : SE
##
## Sample size: 316
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: surprise
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4263 0.1818 2.9768 34.7673 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.3524 0.1684 13.9709 0.0000 2.0211 2.6837
## X1 1.8952 0.2381 7.9591 0.0000 1.4267 2.3638
## X2 1.4589 0.2376 6.1414 0.0000 0.9915 1.9264
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6456 0.4169 2.2599 111.8762 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.1905 0.1467 28.5639 0.0000 3.9018 4.4791
## X1 -2.0381 0.2075 -9.8234 0.0000 -2.4463 -1.6299
## X2 -3.0395 0.2070 -14.6849 0.0000 -3.4468 -2.6323
##
## ***********************************************************************
## Outcome Variable: character
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3237 0.1048 1.2312 18.3180 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0095 0.1083 27.7927 0.0000 2.7965 3.2226
## X1 -0.4762 0.1531 -3.1096 0.0020 -0.7775 -0.1749
## X2 -0.9246 0.1528 -6.0521 0.0000 -1.2252 -0.6240
##
## ***********************************************************************
## Outcome Variable: wrongness
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2315 0.0536 1.5435 8.8612 2.0000 313.0000 0.0002
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.6762 0.1212 38.5688 0.0000 4.4376 4.9147
## X1 0.3714 0.1715 2.1662 0.0310 0.0341 0.7088
## X2 0.7200 0.1711 4.2093 0.0000 0.3835 1.0566
##
## ***********************************************************************
## Outcome Variable: justreasons
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3505 0.1228 1.9082 21.9126 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.7095 0.1348 12.6811 0.0000 1.4443 1.9748
## X1 -0.7762 0.1906 -4.0713 0.0001 -1.1513 -0.4011
## X2 -1.2473 0.1902 -6.5577 0.0000 -1.6215 -0.8730
##
## ***********************************************************************
## Outcome Variable: guilt
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2633 0.0693 1.9793 11.6589 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.4667 0.1373 25.2492 0.0000 3.1965 3.7368
## X1 -0.5619 0.1942 -2.8939 0.0041 -0.9439 -0.1799
## X2 -0.9289 0.1937 -4.7955 0.0000 -1.3101 -0.5478
##
## ***********************************************************************
## Outcome Variable: SFC
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1856 0.0345 1.8593 5.5849 2.0000 313.0000 0.0041
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6095 0.1331 27.1247 0.0000 3.3477 3.8714
## X1 0.5143 0.1882 2.7328 0.0066 0.1440 0.8846
## X2 0.5697 0.1877 3.0345 0.0026 0.2003 0.9391
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2811 0.0790 1.6829 13.4253 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.9143 0.1266 23.0195 0.0000 2.6652 3.1634
## X1 0.4476 0.1790 2.5001 0.0129 0.0953 0.7999
## X2 0.9253 0.1786 5.1806 0.0000 0.5739 1.2768
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6827 0.4661 1.0644 26.6222 10.0000 305.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.3541 0.4611 2.9367 0.0036 0.4468 2.2615
## X1 0.0607 0.1726 0.3516 0.7253 -0.2789 0.4003
## X2 0.0451 0.1890 0.2387 0.8115 -0.3268 0.4170
## surprise 0.1236 0.0352 3.5135 0.0005 0.0544 0.1929
## sympathy -0.1826 0.0465 -3.9233 0.0001 -0.2741 -0.0910
## character -0.0339 0.0606 -0.5596 0.5761 -0.1531 0.0853
## wrongness 0.3606 0.0617 5.8445 0.0000 0.2392 0.4820
## justreasons 0.0909 0.0574 1.5837 0.1143 -0.0221 0.2039
## guilt -0.0554 0.0433 -1.2799 0.2016 -0.1405 0.0298
## SFC 0.1171 0.0491 2.3865 0.0176 0.0205 0.2137
## SE 0.1493 0.0529 2.8240 0.0051 0.0453 0.2534
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3714 0.1379 1.6745 25.0428 2.0000 313.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2857 0.1263 26.0185 0.0000 3.0372 3.5342
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Relative total effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9048 0.1786 5.0661 0.0000 0.5534 1.2562
## X2 1.2143 0.1782 6.8153 0.0000 0.8637 1.5648
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1379 25.0428 2.0000 313.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.0607 0.1726 0.3516 0.7253 -0.2789 0.4003
## X2 0.0451 0.1890 0.2387 0.8115 -0.3268 0.4170
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0002 0.0619 2.0000 305.0000 0.9400
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2343 0.0820 0.0828 0.4047
## X2 0.1804 0.0664 0.0610 0.3230
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2343 0.0734 3.1933 0.0014
## X2 0.1804 0.0597 3.0197 0.0025
##
## ses_origin_ -> sympathy -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3721 0.1037 0.1731 0.5851
## X2 0.5549 0.1489 0.2659 0.8529
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3721 0.1026 3.6273 0.0003
## X2 0.5549 0.1467 3.7822 0.0002
##
## ses_origin_ -> character -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0161 0.0394 -0.0530 0.1061
## X2 0.0313 0.0729 -0.1031 0.1843
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0161 0.0307 0.5251 0.5995
## X2 0.0313 0.0570 0.5499 0.5824
##
## ses_origin_ -> wrongness -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1339 0.0755 0.0030 0.2980
## X2 0.2597 0.0812 0.1219 0.4368
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1339 0.0668 2.0055 0.0449
## X2 0.2597 0.0767 3.3832 0.0007
##
## ses_origin_ -> justreasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0706 0.0460 -0.1795 0.0020
## X2 -0.1134 0.0666 -0.2591 0.0039
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0706 0.0491 -1.4387 0.1502
## X2 -0.1134 0.0745 -1.5228 0.1278
##
## ses_origin_ -> guilt -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0311 0.0315 -0.0267 0.0994
## X2 0.0514 0.0482 -0.0468 0.1452
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0311 0.0279 1.1161 0.2644
## X2 0.0514 0.0424 1.2122 0.2254
##
## ses_origin_ -> SFC -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0602 0.0398 0.0009 0.1544
## X2 0.0667 0.0424 0.0015 0.1652
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0602 0.0348 1.7329 0.0831
## X2 0.0667 0.0367 1.8159 0.0694
##
## ses_origin_ -> SE -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0668 0.0407 0.0031 0.1596
## X2 0.1382 0.0616 0.0216 0.2650
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0668 0.0369 1.8094 0.0704
## X2 0.1382 0.0565 2.4447 0.0145
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000