##
## ********************* 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
## -5.0524 -0.9071 0.0929 0.9476 2.0929
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9071 0.1402 27.860 < 2e-16 ***
## ses_origin_ 0.5726 0.1064 5.379 2.67e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.121 on 157 degrees of freedom
## Multiple R-squared: 0.1556, Adjusted R-squared: 0.1503
## F-statistic: 28.94 on 1 and 157 DF, p-value: 2.668e-07Mediation 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: 159
##
## 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
## 0.3369 0.1135 2.9522 9.9873 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0556 0.2338 13.0682 0.0000 2.5937 3.5174
## X1 1.5069 0.3408 4.4212 0.0000 0.8337 2.1802
## X2 0.5234 0.3263 1.6041 0.1107 -0.1211 1.1679
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4641 0.2154 1.1832 14.1811 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.3427 0.2142 15.6029 0.0000 2.9195 3.7660
## X1 0.6399 0.2289 2.7954 0.0058 0.1877 1.0920
## X2 1.0692 0.2083 5.1341 0.0000 0.6578 1.4806
## surprise 0.1545 0.0507 3.0480 0.0027 0.0544 0.2546
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6399 0.2289 2.7954 0.0058 0.1877 1.0920
## X2 1.0692 0.2083 5.1341 0.0000 0.6578 1.4806
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1338 13.2110 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2328 0.1034 0.0557 0.4636
## X2 0.0809 0.0645 -0.0256 0.2261
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2328 0.0944 2.4670 0.0136
## X2 0.0809 0.0593 1.3632 0.1728
##
## ******************** 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: 159
##
## 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
## 0.5974 0.3568 2.2091 43.2773 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6852 0.2023 18.2201 0.0000 3.2857 4.0847
## X1 -1.5602 0.2948 -5.2916 0.0000 -2.1426 -0.9778
## X2 -2.6150 0.2822 -9.2649 0.0000 -3.1725 -2.0575
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4845 0.2347 1.1540 15.8478 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.5969 0.2585 17.7795 0.0000 4.0861 5.1076
## X1 0.5416 0.2314 2.3401 0.0206 0.0844 0.9988
## X2 0.5952 0.2540 2.3431 0.0204 0.0934 1.0969
## sympathy -0.2122 0.0579 -3.6672 0.0003 -0.3265 -0.0979
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5416 0.2314 2.3401 0.0206 0.0844 0.9988
## X2 0.5952 0.2540 2.3431 0.0204 0.0934 1.0969
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0339 3.4357 2.0000 155.0000 0.0347
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> sympathy -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3311 0.1243 0.1272 0.6048
## X2 0.5549 0.1775 0.2381 0.9355
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3311 0.1112 2.9784 0.0029
## X2 0.5549 0.1636 3.3928 0.0007
##
## ******************** 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: 159
##
## 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
## 0.2920 0.0852 1.2394 7.2683 2.0000 156.0000 0.0010
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8333 0.1515 18.7022 0.0000 2.5341 3.1326
## X1 -0.5833 0.2208 -2.6414 0.0091 -1.0196 -0.1471
## X2 -0.7807 0.2114 -3.6928 0.0003 -1.1983 -0.3631
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4634 0.2148 1.1841 14.1317 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.4862 0.2666 16.8252 0.0000 3.9595 5.0129
## X1 0.7345 0.2206 3.3289 0.0011 0.2986 1.1703
## X2 0.9651 0.2155 4.4788 0.0000 0.5394 1.3908
## character -0.2369 0.0783 -3.0277 0.0029 -0.3915 -0.0824
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7345 0.2206 3.3289 0.0011 0.2986 1.1703
## X2 0.9651 0.2155 4.4788 0.0000 0.5394 1.3908
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1086 10.7155 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> character -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1382 0.0829 0.0120 0.3319
## X2 0.1850 0.0961 0.0248 0.4014
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1382 0.0716 1.9315 0.0534
## X2 0.1850 0.0807 2.2917 0.0219
##
## ******************** 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: 159
##
## 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
## 0.0976 0.0095 1.1873 0.7503 2.0000 156.0000 0.4739
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.2037 0.1483 35.0943 0.0000 4.9108 5.4966
## X1 0.1088 0.2161 0.5033 0.6154 -0.3182 0.5358
## X2 0.2524 0.2069 1.2200 0.2243 -0.1563 0.6612
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5546 0.3076 1.0442 22.9493 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.6335 0.4147 3.9388 0.0001 0.8143 2.4528
## X1 0.8271 0.2029 4.0769 0.0001 0.4263 1.2278
## X2 1.0443 0.1950 5.3560 0.0000 0.6591 1.4294
## wrongness 0.4192 0.0751 5.5827 0.0000 0.2709 0.5675
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8271 0.2029 4.0769 0.0001 0.4263 1.2278
## X2 1.0443 0.1950 5.3560 0.0000 0.6591 1.4294
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1403 15.7082 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> wrongness -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0456 0.1034 -0.1099 0.2941
## X2 0.1058 0.0963 -0.0561 0.3279
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0456 0.0924 0.4935 0.6217
## X2 0.1058 0.0901 1.1740 0.2404
##
## ******************** 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: 159
##
## 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
## 0.1662 0.0276 1.7077 2.2167 2.0000 156.0000 0.1124
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.6296 0.1778 3.5406 0.0005 0.2784 0.9809
## X1 0.3287 0.2592 1.2680 0.2067 -0.1834 0.8408
## X2 -0.2086 0.2482 -0.8405 0.4019 -0.6988 0.2816
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4270 0.1823 1.2331 11.5184 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8845 0.1571 24.7317 0.0000 3.5742 4.1948
## X1 0.9091 0.2214 4.1057 0.0001 0.4717 1.3464
## X2 1.1270 0.2114 5.3324 0.0000 0.7095 1.5445
## justification -0.1107 0.0680 -1.6269 0.1058 -0.2451 0.0237
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9091 0.2214 4.1057 0.0001 0.4717 1.3464
## X2 1.1270 0.2114 5.3324 0.0000 0.7095 1.5445
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1663 15.7602 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justification -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0364 0.0366 -0.1113 0.0366
## X2 0.0231 0.0295 -0.0287 0.0901
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0364 0.0404 -0.8999 0.3682
## X2 0.0231 0.0352 0.6554 0.5122
##
## ******************** 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: 159
##
## 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
## 0.1342 0.0180 1.3506 1.4314 2.0000 156.0000 0.2421
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.5741 0.1582 3.6299 0.0004 0.2617 0.8865
## X1 0.3009 0.2305 1.3053 0.1937 -0.1545 0.7563
## X2 -0.0653 0.2207 -0.2959 0.7677 -0.5012 0.3706
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4321 0.1867 1.2264 11.8644 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8969 0.1569 24.8311 0.0000 3.5869 4.2069
## X1 0.9157 0.2209 4.1457 0.0001 0.4794 1.3520
## X2 1.1408 0.2104 5.4230 0.0000 0.7252 1.5563
## reasons -0.1429 0.0763 -1.8736 0.0629 -0.2936 0.0078
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9157 0.2209 4.1457 0.0001 0.4794 1.3520
## X2 1.1408 0.2104 5.4230 0.0000 0.7252 1.5563
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1699 16.1944 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> reasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0430 0.0426 -0.1386 0.0277
## X2 0.0093 0.0314 -0.0474 0.0819
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0430 0.0438 -0.9810 0.3266
## X2 0.0093 0.0361 0.2585 0.7960
##
## ******************** 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: 159
##
## 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
## 0.1765 0.0311 1.0948 2.5075 2.0000 156.0000 0.0847
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.6019 0.1424 4.2269 0.0000 0.3206 0.8831
## X1 0.3148 0.2076 1.5167 0.1314 -0.0952 0.7248
## X2 -0.1369 0.1987 -0.6892 0.4917 -0.5294 0.2555
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4366 0.1906 1.2206 12.1651 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.9198 0.1587 24.6965 0.0000 3.6063 4.2334
## X1 0.9276 0.2208 4.2017 0.0000 0.4915 1.3637
## X2 1.1262 0.2101 5.3598 0.0000 0.7111 1.5413
## justreasons -0.1745 0.0845 -2.0641 0.0407 -0.3415 -0.0075
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9276 0.2208 4.2017 0.0000 0.4915 1.3637
## X2 1.1262 0.2101 5.3598 0.0000 0.7111 1.5413
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1680 16.0819 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justreasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0549 0.0471 -0.1608 0.0224
## X2 0.0239 0.0335 -0.0435 0.0943
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0549 0.0482 -1.1385 0.2549
## X2 0.0239 0.0402 0.5940 0.5525
##
## ******************** 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: 159
##
## 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
## 0.2012 0.0405 2.0157 3.2896 2.0000 156.0000 0.0399
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2037 0.1932 16.5820 0.0000 2.8221 3.5853
## X1 -0.4745 0.2816 -1.6849 0.0940 -1.0309 0.0818
## X2 -0.6774 0.2696 -2.5125 0.0130 -1.2100 -0.1448
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4733 0.2240 1.1702 14.9154 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.4666 0.2447 18.2554 0.0000 3.9833 4.9499
## X1 0.7761 0.2165 3.5844 0.0005 0.3484 1.2039
## X2 1.0123 0.2095 4.8310 0.0000 0.5984 1.4262
## guilt -0.2034 0.0610 -3.3350 0.0011 -0.3239 -0.0829
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7761 0.2165 3.5844 0.0005 0.3484 1.2039
## X2 1.0123 0.2095 4.8310 0.0000 0.5984 1.4262
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1257 12.5554 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> guilt -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0965 0.0721 -0.0075 0.2703
## X2 0.1378 0.0811 0.0154 0.3257
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0965 0.0665 1.4527 0.1463
## X2 0.1378 0.0706 1.9515 0.0510
##
## ******************** 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: 159
##
## 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
## 0.3868 0.1496 1.9137 13.7253 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.4259 0.1883 12.8866 0.0000 2.0541 2.7978
## X1 1.4074 0.2744 5.1286 0.0000 0.8653 1.9495
## X2 0.9074 0.2627 3.4541 0.0007 0.3885 1.4263
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4118 0.1696 1.2522 10.5528 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.7382 0.2188 17.0850 0.0000 3.3060 4.1704
## X1 0.8282 0.2400 3.4515 0.0007 0.3542 1.3023
## X2 1.1214 0.2205 5.0864 0.0000 0.6859 1.5570
## emo_sup 0.0316 0.0648 0.4875 0.6266 -0.0964 0.1595
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8282 0.2400 3.4515 0.0007 0.3542 1.3023
## X2 1.1214 0.2205 5.0864 0.0000 0.6859 1.5570
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1424 13.2884 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> emo_sup -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0444 0.0995 -0.1570 0.2370
## X2 0.0287 0.0659 -0.1056 0.1574
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0444 0.0933 0.4764 0.6338
## X2 0.0287 0.0617 0.4640 0.6426
##
## ******************** 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: 159
##
## 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
## 0.3356 0.1126 2.0789 9.9013 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.5556 0.1962 18.1210 0.0000 3.1680 3.9431
## X1 -1.2222 0.2860 -4.2731 0.0000 -1.7872 -0.6572
## X2 -0.8713 0.2738 -3.1823 0.0018 -1.4122 -0.3305
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4107 0.1687 1.2536 10.4829 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8705 0.2685 14.4162 0.0000 3.3401 4.4008
## X1 0.8536 0.2347 3.6361 0.0004 0.3898 1.3173
## X2 1.1365 0.2194 5.1795 0.0000 0.7030 1.5699
## abuse -0.0157 0.0622 -0.2517 0.8016 -0.1385 0.1072
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8536 0.2347 3.6361 0.0004 0.3898 1.3173
## X2 1.1365 0.2194 5.1795 0.0000 0.7030 1.5699
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1498 13.9618 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> abuse -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0191 0.0853 -0.1564 0.1901
## X2 0.0136 0.0608 -0.1188 0.1286
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0191 0.0782 0.2447 0.8067
## X2 0.0136 0.0569 0.2395 0.8107
##
## ******************** 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: 159
##
## 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
## 0.1162 0.0135 1.7072 1.0680 2.0000 156.0000 0.3462
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0000 0.1778 22.4968 0.0000 3.6488 4.3512
## X1 -0.0000 0.2592 -0.0000 1.0000 -0.5120 0.5120
## X2 0.3158 0.2481 1.2727 0.2050 -0.1743 0.8059
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5054 0.2554 1.1228 17.7246 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7089 0.2971 9.1188 0.0000 2.1221 3.2957
## X1 0.8727 0.2102 4.1517 0.0001 0.4575 1.2879
## X2 1.0628 0.2023 5.2544 0.0000 0.6632 1.4623
## SFC 0.2765 0.0649 4.2581 0.0000 0.1482 0.4047
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8727 0.2102 4.1517 0.0001 0.4575 1.2879
## X2 1.0628 0.2023 5.2544 0.0000 0.6632 1.4623
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1484 15.4493 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SFC -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0000 0.0720 -0.1328 0.1587
## X2 0.0873 0.0807 -0.0502 0.2726
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0000 0.0736 -0.0000 1.0000
## X2 0.0873 0.0734 1.1897 0.2342
##
## ******************** 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: 159
##
## 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
## 0.2626 0.0689 1.6061 5.7762 2.0000 156.0000 0.0038
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2778 0.1725 19.0059 0.0000 2.9371 3.6184
## X1 0.2222 0.2514 0.8839 0.3781 -0.2744 0.7188
## X2 0.7924 0.2407 3.2925 0.0012 0.3170 1.2678
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4959 0.2459 1.1371 16.8517 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.9328 0.2642 11.0996 0.0000 2.4109 3.4548
## X1 0.8129 0.2121 3.8332 0.0002 0.3940 1.2318
## X2 0.9369 0.2094 4.4737 0.0000 0.5232 1.3506
## SE 0.2691 0.0674 3.9942 0.0001 0.1360 0.4022
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8129 0.2121 3.8332 0.0002 0.3940 1.2318
## X2 0.9369 0.2094 4.4737 0.0000 0.5232 1.3506
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1145 11.7634 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SE -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0598 0.0825 -0.0737 0.2549
## X2 0.2132 0.0947 0.0606 0.4212
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0598 0.0713 0.8384 0.4018
## X2 0.2132 0.0855 2.4945 0.0126
##
## ******************** 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: 159
##
## 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
## 0.3311 0.1096 2.0941 9.6059 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0741 0.1969 20.6882 0.0000 3.6851 4.4631
## X1 -1.2407 0.2871 -4.3221 0.0000 -1.8078 -0.6737
## X2 -0.7583 0.2748 -2.7593 0.0065 -1.3011 -0.2155
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4107 0.1687 1.2536 10.4833 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8788 0.2948 13.1572 0.0000 3.2964 4.4611
## X1 0.8532 0.2350 3.6302 0.0004 0.3889 1.3175
## X2 1.1382 0.2177 5.2271 0.0000 0.7081 1.5683
## upbringing -0.0157 0.0619 -0.2534 0.8003 -0.1381 0.1067
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.8532 0.2350 3.6302 0.0004 0.3889 1.3175
## X2 1.1382 0.2177 5.2271 0.0000 0.7081 1.5683
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1524 14.2078 2.0000 155.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> upbringing -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0195 0.0684 -0.1090 0.1636
## X2 0.0119 0.0423 -0.0706 0.1008
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0195 0.0790 0.2465 0.8053
## X2 0.0119 0.0501 0.2373 0.8124
##
## ******************** 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 wrongness, justification, reasons, emo_sup, abuse, SFC, 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 : guilt
## M5 : SE
##
## Sample size: 159
##
## 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
## 0.3369 0.1135 2.9522 9.9873 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0556 0.2338 13.0682 0.0000 2.5937 3.5174
## X1 1.5069 0.3408 4.4212 0.0000 0.8337 2.1802
## X2 0.5234 0.3263 1.6041 0.1107 -0.1211 1.1679
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5974 0.3568 2.2091 43.2773 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6852 0.2023 18.2201 0.0000 3.2857 4.0847
## X1 -1.5602 0.2948 -5.2916 0.0000 -2.1426 -0.9778
## X2 -2.6150 0.2822 -9.2649 0.0000 -3.1725 -2.0575
##
## ***********************************************************************
## Outcome Variable: character
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2920 0.0852 1.2394 7.2683 2.0000 156.0000 0.0010
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8333 0.1515 18.7022 0.0000 2.5341 3.1326
## X1 -0.5833 0.2208 -2.6414 0.0091 -1.0196 -0.1471
## X2 -0.7807 0.2114 -3.6928 0.0003 -1.1983 -0.3631
##
## ***********************************************************************
## Outcome Variable: guilt
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2012 0.0405 2.0157 3.2896 2.0000 156.0000 0.0399
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2037 0.1932 16.5820 0.0000 2.8221 3.5853
## X1 -0.4745 0.2816 -1.6849 0.0940 -1.0309 0.0818
## X2 -0.6774 0.2696 -2.5125 0.0130 -1.2100 -0.1448
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2626 0.0689 1.6061 5.7762 2.0000 156.0000 0.0038
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2778 0.1725 19.0059 0.0000 2.9371 3.6184
## X1 0.2222 0.2514 0.8839 0.3781 -0.2744 0.7188
## X2 0.7924 0.2407 3.2925 0.0012 0.3170 1.2678
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5971 0.3565 0.9961 11.9508 7.0000 151.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.9566 0.4569 8.6592 0.0000 3.0538 4.8594
## X1 0.3263 0.2269 1.4384 0.1524 -0.1219 0.7745
## X2 0.4360 0.2379 1.8327 0.0688 -0.0340 0.9061
## surprise 0.1262 0.0470 2.6876 0.0080 0.0334 0.2190
## sympathy -0.1352 0.0582 -2.3224 0.0215 -0.2502 -0.0202
## character -0.0464 0.0814 -0.5700 0.5695 -0.2072 0.1144
## guilt -0.1608 0.0578 -2.7845 0.0060 -0.2750 -0.0467
## SE 0.1884 0.0687 2.7430 0.0068 0.0527 0.3241
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4103 0.1683 1.2461 15.7875 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8148 0.1519 25.1128 0.0000 3.5148 4.1149
## X1 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## ***********************************************************************
## 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 0.8727 0.2214 3.9409 0.0001 0.4353 1.3101
## X2 1.1501 0.2120 5.4254 0.0000 0.7314 1.5688
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1683 15.7875 2.0000 156.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.3263 0.2269 1.4384 0.1524 -0.1219 0.7745
## X2 0.4360 0.2379 1.8327 0.0688 -0.0340 0.9061
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0152 1.7796 2.0000 151.0000 0.1722
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1902 0.0912 0.0271 0.3855
## X2 0.0661 0.0524 -0.0209 0.1834
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1902 0.0843 2.2549 0.0241
## X2 0.0661 0.0503 1.3121 0.1895
##
## ses_origin_ -> sympathy -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2109 0.1064 0.0255 0.4389
## X2 0.3536 0.1658 0.0446 0.6974
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2109 0.1007 2.0954 0.0361
## X2 0.3536 0.1578 2.2404 0.0251
##
## ses_origin_ -> character -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0271 0.0657 -0.0903 0.1808
## X2 0.0362 0.0844 -0.1161 0.2232
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0271 0.0518 0.5226 0.6013
## X2 0.0362 0.0665 0.5442 0.5863
##
## ses_origin_ -> guilt -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0763 0.0602 -0.0068 0.2249
## X2 0.1089 0.0677 0.0076 0.2691
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0763 0.0554 1.3780 0.1682
## X2 0.1089 0.0604 1.8024 0.0715
##
## ses_origin_ -> SE -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0419 0.0586 -0.0576 0.1768
## X2 0.1493 0.0756 0.0207 0.3174
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0419 0.0527 0.7948 0.4267
## X2 0.1493 0.0727 2.0523 0.0401
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000