##
## ********************* 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
## -3.1183 -0.8784 0.1216 0.8817 2.5017
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.8784 0.1634 17.613 < 2e-16 ***
## ses_origin_ 0.6200 0.1287 4.816 3.46e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.287 on 155 degrees of freedom
## Multiple R-squared: 0.1302, Adjusted R-squared: 0.1245
## F-statistic: 23.19 on 1 and 155 DF, p-value: 3.458e-06Mediation 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: 157
##
## 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
## 0.5789 0.3351 2.6027 38.8042 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.6078 0.2259 7.1174 0.0000 1.1616 2.0541
## X1 2.3746 0.3110 7.6365 0.0000 1.7603 2.9889
## X2 2.4738 0.3227 7.6654 0.0000 1.8363 3.1113
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4483 0.2009 1.5419 12.8255 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.4228 0.2004 12.0874 0.0000 2.0268 2.8188
## X1 0.5995 0.2810 2.1331 0.0345 0.0443 1.1547
## X2 0.7681 0.2920 2.6307 0.0094 0.1913 1.3449
## surprise 0.1882 0.0620 3.0348 0.0028 0.0657 0.3108
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5995 0.2810 2.1331 0.0345 0.0443 1.1547
## X2 0.7681 0.2920 2.6307 0.0094 0.1913 1.3449
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0379 3.6250 2.0000 153.0000 0.0290
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.4470 0.1684 0.1440 0.8060
## X2 0.4656 0.1825 0.1461 0.8660
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.4470 0.1597 2.7996 0.0051
## X2 0.4656 0.1662 2.8012 0.0051
##
## ******************** 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: 157
##
## 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
## 0.7045 0.4964 2.1653 75.8857 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.7255 0.2061 22.9334 0.0000 4.3184 5.1325
## X1 -2.5501 0.2836 -8.9907 0.0000 -3.1104 -1.9897
## X2 -3.4806 0.2944 -11.8242 0.0000 -4.0621 -2.8991
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5493 0.3017 1.3474 22.0385 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.4412 0.3415 13.0036 0.0000 3.7665 5.1159
## X1 0.1206 0.2763 0.4364 0.6631 -0.4252 0.6664
## X2 -0.0300 0.3207 -0.0936 0.9255 -0.6637 0.6036
## sympathy -0.3631 0.0636 -5.7118 0.0000 -0.4887 -0.2375
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.1206 0.2763 0.4364 0.6631 -0.4252 0.6664
## X2 -0.0300 0.3207 -0.0936 0.9255 -0.6637 0.6036
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0023 0.2536 2.0000 153.0000 0.7763
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> sympathy -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.9259 0.1964 0.5776 1.3453
## X2 1.2637 0.2192 0.8472 1.7069
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.9259 0.1929 4.8001 0.0000
## X2 1.2637 0.2464 5.1283 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: 157
##
## 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
## 0.3723 0.1386 1.1775 12.3915 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.1961 0.1520 21.0337 0.0000 2.8959 3.4963
## X1 -0.4241 0.2092 -2.0279 0.0443 -0.8373 -0.0110
## X2 -1.0736 0.2171 -4.9460 0.0000 -1.5025 -0.6448
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4691 0.2200 1.5051 14.3872 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.7825 0.3381 11.1886 0.0000 3.1146 4.4504
## X1 0.9062 0.2396 3.7819 0.0002 0.4328 1.3795
## X2 0.8786 0.2642 3.3257 0.0011 0.3567 1.4005
## character -0.3307 0.0911 -3.6303 0.0004 -0.5107 -0.1508
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9062 0.2396 3.7819 0.0002 0.4328 1.3795
## X2 0.8786 0.2642 3.3257 0.0011 0.3567 1.4005
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0855 8.3866 2.0000 153.0000 0.0003
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> character -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1403 0.0866 0.0100 0.3433
## X2 0.3551 0.1500 0.0969 0.6753
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1403 0.0815 1.7213 0.0852
## X2 0.3551 0.1229 2.8885 0.0039
##
## ******************** 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: 157
##
## 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
## 0.3528 0.1244 1.6904 10.9435 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.1176 0.1821 22.6175 0.0000 3.7580 4.4773
## X1 0.7069 0.2506 2.8209 0.0054 0.2119 1.2020
## X2 1.2089 0.2601 4.6481 0.0000 0.6951 1.7227
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5675 0.3220 1.3083 24.2214 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.9219 0.3330 2.7689 0.0063 0.2641 1.5797
## X1 0.7368 0.2261 3.2589 0.0014 0.2901 1.1835
## X2 0.7042 0.2443 2.8821 0.0045 0.2215 1.1869
## wrongness 0.4380 0.0709 6.1784 0.0000 0.2979 0.5781
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7368 0.2261 3.2589 0.0014 0.2901 1.1835
## X2 0.7042 0.2443 2.8821 0.0045 0.2215 1.1869
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0549 6.1912 2.0000 153.0000 0.0026
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> wrongness -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3096 0.1362 0.0680 0.6021
## X2 0.5295 0.1517 0.2620 0.8605
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3096 0.1220 2.5387 0.0111
## X2 0.5295 0.1437 3.6837 0.0002
##
## ******************** 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: 157
##
## 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
## 0.5062 0.2562 2.1186 26.5220 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.3725 0.2038 11.6407 0.0000 1.9699 2.7752
## X1 -1.4076 0.2806 -5.0174 0.0000 -1.9619 -0.8534
## X2 -2.0664 0.2912 -7.0971 0.0000 -2.6416 -1.4912
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4748 0.2255 1.4946 14.8448 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.3336 0.2347 14.2027 0.0000 2.8699 3.7973
## X1 0.6856 0.2542 2.6975 0.0078 0.1835 1.1878
## X2 0.7040 0.2817 2.4989 0.0135 0.1474 1.2606
## justification -0.2563 0.0677 -3.7871 0.0002 -0.3900 -0.1226
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6856 0.2542 2.6975 0.0078 0.1835 1.1878
## X2 0.7040 0.2817 2.4989 0.0135 0.1474 1.2606
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0431 4.2559 2.0000 153.0000 0.0159
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justification -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3608 0.1415 0.1265 0.6785
## X2 0.5297 0.1600 0.2396 0.8660
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3608 0.1209 2.9852 0.0028
## X2 0.5297 0.1597 3.3157 0.0009
##
## ******************** 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: 157
##
## 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
## 0.6446 0.4155 2.1656 54.7331 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.3922 0.2061 16.4614 0.0000 2.9851 3.7992
## X1 -2.4623 0.2836 -8.6809 0.0000 -3.0227 -1.9020
## X2 -2.7799 0.2944 -9.4432 0.0000 -3.3615 -2.1984
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4988 0.2488 1.4496 16.8907 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.7141 0.2801 13.2616 0.0000 3.1608 4.2674
## X1 0.3288 0.2832 1.1611 0.2474 -0.2307 0.8883
## X2 0.4235 0.3026 1.3994 0.1637 -0.1744 1.0214
## reasons -0.2914 0.0659 -4.4206 0.0000 -0.4217 -0.1612
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.3288 0.2832 1.1611 0.2474 -0.2307 0.8883
## X2 0.4235 0.3026 1.3994 0.1637 -0.1744 1.0214
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0100 1.0205 2.0000 153.0000 0.3628
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> reasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.7176 0.2027 0.3672 1.1568
## X2 0.8102 0.2095 0.4352 1.2486
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.7176 0.1831 3.9187 0.0001
## X2 0.8102 0.2033 3.9854 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_ -> 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: 157
##
## 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
## 0.6045 0.3654 1.8835 44.3405 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8824 0.1922 14.9987 0.0000 2.5027 3.2620
## X1 -1.9350 0.2645 -7.3149 0.0000 -2.4576 -1.4124
## X2 -2.4232 0.2745 -8.8265 0.0000 -2.9655 -1.8808
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4983 0.2483 1.4505 16.8465 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6239 0.2646 13.6984 0.0000 3.1013 4.1466
## X1 0.4433 0.2695 1.6450 0.1020 -0.0891 0.9756
## X2 0.4784 0.2956 1.6180 0.1077 -0.1057 1.0624
## justreasons -0.3117 0.0707 -4.4079 0.0000 -0.4514 -0.1720
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.4433 0.2695 1.6450 0.1020 -0.0891 0.9756
## X2 0.4784 0.2956 1.6180 0.1077 -0.1057 1.0624
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0158 1.6125 2.0000 153.0000 0.2028
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justreasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.6032 0.1843 0.2882 1.0064
## X2 0.7553 0.1959 0.4035 1.1740
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.6032 0.1608 3.7498 0.0002
## X2 0.7553 0.1925 3.9234 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_ -> 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: 157
##
## 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
## 0.3302 0.1090 1.9133 9.4208 2.0000 154.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.7451 0.1937 19.3355 0.0000 3.3625 4.1277
## X1 -0.6925 0.2666 -2.5973 0.0103 -1.2192 -0.1658
## X2 -1.1941 0.2767 -4.3154 0.0000 -1.7407 -0.6475
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3918 0.1535 1.6334 9.2510 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8244 0.3313 8.5246 0.0000 2.1698 3.4790
## X1 1.0282 0.2517 4.0852 0.0001 0.5309 1.5254
## X2 1.2022 0.2707 4.4413 0.0000 0.6674 1.7369
## guilt -0.0264 0.0745 -0.3547 0.7233 -0.1735 0.1207
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.0282 0.2517 4.0852 0.0001 0.5309 1.5254
## X2 1.2022 0.2707 4.4413 0.0000 0.6674 1.7369
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1316 11.8906 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> guilt -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0183 0.0633 -0.0990 0.1562
## X2 0.0315 0.1055 -0.1861 0.2384
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0183 0.0557 0.3284 0.7426
## X2 0.0315 0.0916 0.3445 0.7305
##
## ******************** 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: 157
##
## 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
## 0.3557 0.1265 1.6623 11.1505 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8627 0.1805 15.8566 0.0000 2.5061 3.2194
## X1 1.1373 0.2485 4.5763 0.0000 0.6463 1.6282
## X2 0.3413 0.2579 1.3235 0.1876 -0.1682 0.8508
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3922 0.1538 1.6329 9.2697 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8207 0.2903 9.7156 0.0000 2.2471 3.3943
## X1 1.0843 0.2625 4.1303 0.0001 0.5656 1.6029
## X2 1.2450 0.2571 4.8433 0.0000 0.7372 1.7529
## emo_sup -0.0333 0.0799 -0.4164 0.6777 -0.1910 0.1245
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.0843 0.2625 4.1303 0.0001 0.5656 1.6029
## X2 1.2450 0.2571 4.8433 0.0000 0.7372 1.7529
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1502 13.5819 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> emo_sup -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0378 0.0926 -0.2303 0.1411
## X2 -0.0114 0.0359 -0.1026 0.0475
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0378 0.0933 -0.4052 0.6853
## X2 -0.0114 0.0352 -0.3222 0.7473
##
## ******************** 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: 157
##
## 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
## 0.3725 0.1387 2.1929 12.4044 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.4118 0.2074 16.4535 0.0000 3.0021 3.8214
## X1 -1.4118 0.2854 -4.9462 0.0000 -1.9756 -0.8479
## X2 -0.5954 0.2962 -2.0101 0.0462 -1.1806 -0.0102
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3949 0.1560 1.6287 9.4232 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.9033 0.2968 9.7829 0.0000 2.3170 3.4896
## X1 0.9729 0.2648 3.6738 0.0003 0.4497 1.4960
## X2 1.2027 0.2586 4.6503 0.0000 0.6917 1.7136
## abuse -0.0521 0.0694 -0.7506 0.4541 -0.1893 0.0851
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9729 0.2648 3.6738 0.0003 0.4497 1.4960
## X2 1.2027 0.2586 4.6503 0.0000 0.6917 1.7136
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1308 11.8576 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> abuse -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0736 0.1053 -0.1175 0.2994
## X2 0.0310 0.0503 -0.0553 0.1485
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0736 0.1011 0.7277 0.4668
## X2 0.0310 0.0487 0.6373 0.5239
##
## ******************** 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: 157
##
## 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
## 0.3097 0.0959 1.9159 8.1691 2.0000 154.0000 0.0004
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.1961 0.1938 16.4897 0.0000 2.8132 3.5790
## X1 1.0320 0.2668 3.8681 0.0002 0.5049 1.5590
## X2 0.8243 0.2769 2.9771 0.0034 0.2773 1.3713
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5349 0.2861 1.3775 20.4413 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.5583 0.2733 5.7015 0.0000 1.0184 2.0983
## X1 0.6696 0.2370 2.8257 0.0053 0.2014 1.1377
## X2 0.9327 0.2414 3.8628 0.0002 0.4557 1.4097
## SFC 0.3652 0.0683 5.3447 0.0000 0.2302 0.5002
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6696 0.2370 2.8257 0.0053 0.2014 1.1377
## X2 0.9327 0.2414 3.8628 0.0002 0.4557 1.4097
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0732 7.8417 2.0000 153.0000 0.0006
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SFC -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3769 0.1277 0.1588 0.6632
## X2 0.3010 0.1294 0.0729 0.5843
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3769 0.1216 3.0982 0.0019
## X2 0.3010 0.1173 2.5668 0.0103
##
## ******************** 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: 157
##
## 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
## 0.3189 0.1017 1.6446 8.7161 2.0000 154.0000 0.0003
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.5294 0.1796 14.0856 0.0000 2.1747 2.8842
## X1 0.7162 0.2472 2.8975 0.0043 0.2279 1.2045
## X2 1.0420 0.2565 4.0619 0.0001 0.5352 1.5488
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5422 0.2940 1.3623 21.2413 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.6993 0.2472 6.8734 0.0000 1.2109 2.1878
## X1 0.7559 0.2310 3.2720 0.0013 0.2995 1.2123
## X2 0.8110 0.2457 3.3010 0.0012 0.3256 1.2963
## SE 0.4057 0.0733 5.5316 0.0000 0.2608 0.5506
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7559 0.2310 3.2720 0.0013 0.2995 1.2123
## X2 0.8110 0.2457 3.3010 0.0012 0.3256 1.2963
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0647 7.0079 2.0000 153.0000 0.0012
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SE -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2906 0.1185 0.0882 0.5463
## X2 0.4227 0.1478 0.1684 0.7385
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2906 0.1146 2.5344 0.0113
## X2 0.4227 0.1305 3.2398 0.0012
##
## ******************** 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: 157
##
## 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
## 0.3528 0.1245 1.8339 10.9492 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.3333 0.1896 22.8520 0.0000 3.9587 4.7079
## X1 -1.1930 0.2610 -4.5705 0.0000 -1.7086 -0.6773
## X2 -0.8639 0.2709 -3.1892 0.0017 -1.3991 -0.3288
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4060 0.1648 1.6116 10.0631 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2099 0.3725 8.6171 0.0000 2.4740 3.9458
## X1 0.9131 0.2608 3.5016 0.0006 0.3979 1.4282
## X2 1.1371 0.2622 4.3368 0.0000 0.6191 1.6551
## upbringing -0.1118 0.0755 -1.4798 0.1410 -0.2610 0.0375
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9131 0.2608 3.5016 0.0006 0.3979 1.4282
## X2 1.1371 0.2622 4.3368 0.0000 0.6191 1.6551
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1125 10.3071 2.0000 153.0000 0.0001
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> upbringing -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1334 0.0929 -0.0255 0.3362
## X2 0.0966 0.0717 -0.0168 0.2621
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1334 0.0968 1.3783 0.1681
## X2 0.0966 0.0748 1.2911 0.1967
##
## ******************** 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 guilt, 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 : SFC
## M7 : SE
##
## Sample size: 157
##
## 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
## 0.5789 0.3351 2.6027 38.8042 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.6078 0.2259 7.1174 0.0000 1.1616 2.0541
## X1 2.3746 0.3110 7.6365 0.0000 1.7603 2.9889
## X2 2.4738 0.3227 7.6654 0.0000 1.8363 3.1113
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7045 0.4964 2.1653 75.8857 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.7255 0.2061 22.9334 0.0000 4.3184 5.1325
## X1 -2.5501 0.2836 -8.9907 0.0000 -3.1104 -1.9897
## X2 -3.4806 0.2944 -11.8242 0.0000 -4.0621 -2.8991
##
## ***********************************************************************
## Outcome Variable: character
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3723 0.1386 1.1775 12.3915 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.1961 0.1520 21.0337 0.0000 2.8959 3.4963
## X1 -0.4241 0.2092 -2.0279 0.0443 -0.8373 -0.0110
## X2 -1.0736 0.2171 -4.9460 0.0000 -1.5025 -0.6448
##
## ***********************************************************************
## Outcome Variable: wrongness
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3528 0.1244 1.6904 10.9435 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.1176 0.1821 22.6175 0.0000 3.7580 4.4773
## X1 0.7069 0.2506 2.8209 0.0054 0.2119 1.2020
## X2 1.2089 0.2601 4.6481 0.0000 0.6951 1.7227
##
## ***********************************************************************
## Outcome Variable: justreasons
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6045 0.3654 1.8835 44.3405 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8824 0.1922 14.9987 0.0000 2.5027 3.2620
## X1 -1.9350 0.2645 -7.3149 0.0000 -2.4576 -1.4124
## X2 -2.4232 0.2745 -8.8265 0.0000 -2.9655 -1.8808
##
## ***********************************************************************
## Outcome Variable: SFC
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3097 0.0959 1.9159 8.1691 2.0000 154.0000 0.0004
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.1961 0.1938 16.4897 0.0000 2.8132 3.5790
## X1 1.0320 0.2668 3.8681 0.0002 0.5049 1.5590
## X2 0.8243 0.2769 2.9771 0.0034 0.2773 1.3713
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3189 0.1017 1.6446 8.7161 2.0000 154.0000 0.0003
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.5294 0.1796 14.0856 0.0000 2.1747 2.8842
## X1 0.7162 0.2472 2.8975 0.0043 0.2279 1.2045
## X2 1.0420 0.2565 4.0619 0.0001 0.5352 1.5488
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6965 0.4851 1.0340 15.3904 9.0000 147.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.1646 0.6564 1.7743 0.0781 -0.1326 2.4618
## X1 -0.0788 0.2756 -0.2859 0.7754 -0.6235 0.4659
## X2 -0.3047 0.3080 -0.9892 0.3242 -0.9135 0.3041
## surprise 0.0965 0.0544 1.7724 0.0784 -0.0111 0.2040
## sympathy -0.2463 0.0688 -3.5801 0.0005 -0.3822 -0.1103
## character -0.0069 0.0892 -0.0775 0.9383 -0.1832 0.1694
## wrongness 0.3519 0.0859 4.0972 0.0001 0.1821 0.5216
## justreasons 0.1157 0.0867 1.3343 0.1842 -0.0556 0.2870
## SFC 0.0879 0.0707 1.2438 0.2156 -0.0518 0.2276
## SE 0.2089 0.0732 2.8546 0.0049 0.0643 0.3535
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3910 0.1528 1.6241 13.8925 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.7255 0.1785 15.2730 0.0000 2.3730 3.0780
## X1 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## ***********************************************************************
## 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 1.0464 0.2456 4.2601 0.0000 0.5612 1.5317
## X2 1.2337 0.2549 4.8393 0.0000 0.7301 1.7373
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.1528 13.8925 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.0788 0.2756 -0.2859 0.7754 -0.6235 0.4659
## X2 -0.3047 0.3080 -0.9892 0.3242 -0.9135 0.3041
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0050 0.7067 2.0000 147.0000 0.4949
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2291 0.1342 -0.0269 0.5043
## X2 0.2386 0.1429 -0.0271 0.5381
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2291 0.1337 1.7126 0.0868
## X2 0.2386 0.1393 1.7130 0.0867
##
## ses_origin_ -> sympathy -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.6280 0.2031 0.2446 1.0382
## X2 0.8572 0.2599 0.3393 1.3570
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.6280 0.1898 3.3085 0.0009
## X2 0.8572 0.2510 3.4153 0.0006
##
## ses_origin_ -> character -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0029 0.0516 -0.0887 0.1281
## X2 0.0074 0.1216 -0.2015 0.2808
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0029 0.0422 0.0695 0.9446
## X2 0.0074 0.0977 0.0759 0.9395
##
## ses_origin_ -> wrongness -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2487 0.1191 0.0516 0.5175
## X2 0.4254 0.1404 0.1877 0.7347
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2487 0.1092 2.2779 0.0227
## X2 0.4254 0.1402 3.0343 0.0024
##
## ses_origin_ -> justreasons -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.2238 0.1624 -0.5849 0.0592
## X2 -0.2803 0.2011 -0.7224 0.0735
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.2238 0.1720 -1.3009 0.1933
## X2 -0.2803 0.2138 -1.3111 0.1898
##
## ses_origin_ -> SFC -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0907 0.0861 -0.0627 0.2805
## X2 0.0725 0.0716 -0.0517 0.2332
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0907 0.0789 1.1498 0.2502
## X2 0.0725 0.0661 1.0962 0.2730
##
## ses_origin_ -> SE -> punishment
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1496 0.0834 0.0163 0.3399
## X2 0.2177 0.1077 0.0315 0.4521
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1496 0.0758 1.9747 0.0483
## X2 0.2177 0.0951 2.2895 0.0220
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000