##
## ********************* 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
## X1: poor-middle_class
X2: poor-rich
Condition (X1 or X2) as antecedent variable.
##
## Call:
## lm(formula = punish_post ~ condition_1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.8456 -0.8456 0.0242 1.0242 1.1544
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.84556 0.09811 49.390 <2e-16 ***
## condition_1 0.13024 0.07569 1.721 0.0863 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.07 on 298 degrees of freedom
## Multiple R-squared: 0.009838, Adjusted R-squared: 0.006515
## F-statistic: 2.961 on 1 and 298 DF, p-value: 0.08635Mediation analysis: condition -> character -> punish_post
##
## ********************* 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 : punish_post
## X : condition_1
## M : character
##
## Sample size: 300
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## condition_1 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
## 0.1679 0.0282 1.5555 4.3099 2.0000 297.0000 0.0143
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.3535 0.1253 18.7759 0.0000 2.1069 2.6002
## X1 -0.1435 0.1768 -0.8117 0.4176 -0.4915 0.2045
## X2 -0.5021 0.1764 -2.8463 0.0047 -0.8492 -0.1549
##
## ***********************************************************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4073 0.1659 0.9717 19.6286 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.6415 0.1465 38.5059 0.0000 5.3532 5.9298
## X1 0.1026 0.1399 0.7336 0.4638 -0.1727 0.3780
## X2 0.0893 0.1413 0.6320 0.5278 -0.1888 0.3674
## character -0.3412 0.0459 -7.4407 0.0000 -0.4315 -0.2510
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0996 0.0099 1.1495 1.4887 2.0000 297.0000 0.2273
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8384 0.1078 44.9009 0.0000 4.6263 5.0504
## X1 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## ***********************************************************************
## 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 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0099 1.4887 2.0000 297.0000 0.2273
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.1026 0.1399 0.7336 0.4638 -0.1727 0.3780
## X2 0.0893 0.1413 0.6320 0.5278 -0.1888 0.3674
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0018 0.3152 2.0000 296.0000 0.7299
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> character -> punish_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0490 0.0617 -0.0680 0.1740
## X2 0.1713 0.0685 0.0501 0.3189
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0490 0.0612 0.7998 0.4238
## X2 0.1713 0.0650 2.6377 0.0083
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: condition -> wrongness -> punish_post
##
## ********************* 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 : punish_post
## X : condition_1
## M : wrongness
##
## Sample size: 300
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## condition_1 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
## 0.1004 0.0101 0.5830 1.5120 2.0000 297.0000 0.2222
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.5758 0.0767 72.6581 0.0000 5.4247 5.7268
## X1 0.1442 0.1083 1.3324 0.1837 -0.0688 0.3573
## X2 0.1767 0.1080 1.6365 0.1028 -0.0358 0.3892
##
## ***********************************************************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3713 0.1379 1.0044 15.7797 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.0238 0.4364 4.6370 0.0000 1.1649 2.8827
## X1 0.0788 0.1425 0.5530 0.5807 -0.2017 0.3593
## X2 0.1714 0.1424 1.2040 0.2295 -0.1088 0.4516
## wrongness 0.5048 0.0762 6.6281 0.0000 0.3549 0.6547
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0996 0.0099 1.1495 1.4887 2.0000 297.0000 0.2273
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8384 0.1078 44.9009 0.0000 4.6263 5.0504
## X1 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## ***********************************************************************
## 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 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0099 1.4887 2.0000 297.0000 0.2273
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.0788 0.1425 0.5530 0.5807 -0.2017 0.3593
## X2 0.1714 0.1424 1.2040 0.2295 -0.1088 0.4516
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0042 0.7271 2.0000 296.0000 0.4842
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> wrongness -> punish_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0728 0.0620 -0.0302 0.2152
## X2 0.0892 0.0720 -0.0178 0.2554
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0728 0.0563 1.2922 0.1963
## X2 0.0892 0.0567 1.5720 0.1160
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: condition -> justification -> punish_post
##
## ********************* 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 : punish_post
## X : condition_1
## M : justification
##
## Sample size: 300
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## condition_1 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
## 0.0920 0.0085 1.3913 1.2681 2.0000 297.0000 0.2829
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.6465 0.1185 5.4532 0.0000 0.4132 0.8798
## X1 0.0335 0.1672 0.2005 0.8412 -0.2956 0.3626
## X2 -0.2108 0.1668 -1.2638 0.2073 -0.5391 0.1175
##
## ***********************************************************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4157 0.1728 0.9637 20.6081 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0767 0.1035 49.0576 0.0000 4.8730 5.2804
## X1 0.1640 0.1392 1.1781 0.2397 -0.1099 0.4379
## X2 0.1829 0.1392 1.3139 0.1899 -0.0911 0.4569
## justification -0.3687 0.0483 -7.6337 0.0000 -0.4637 -0.2736
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0996 0.0099 1.1495 1.4887 2.0000 297.0000 0.2273
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8384 0.1078 44.9009 0.0000 4.6263 5.0504
## X1 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## ***********************************************************************
## 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 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0099 1.4887 2.0000 297.0000 0.2273
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.1640 0.1392 1.1781 0.2397 -0.1099 0.4379
## X2 0.1829 0.1392 1.3139 0.1899 -0.0911 0.4569
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0058 1.0432 2.0000 296.0000 0.3536
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> justification -> punish_post
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0124 0.0673 -0.1406 0.1281
## X2 0.0777 0.0625 -0.0328 0.2097
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0124 0.0622 -0.1988 0.8424
## X2 0.0777 0.0629 1.2365 0.2163
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: manip_check -> justification -> blame_post
Mediation analysis: condition -> guilt -> punish_post
##
## ********************* 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 : punish_post
## X : condition_1
## M : guilt
##
## Sample size: 300
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## condition_1 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
## 0.2391 0.0572 2.7366 9.0065 2.0000 297.0000 0.0002
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.2525 0.1663 25.5773 0.0000 3.9253 4.5797
## X1 0.2175 0.2345 0.9272 0.3546 -0.2441 0.6790
## X2 -0.7278 0.2340 -3.1106 0.0020 -1.1882 -0.2673
##
## ***********************************************************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1622 0.0263 1.1344 2.6646 3.0000 296.0000 0.0481
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.1928 0.1916 27.1073 0.0000 4.8158 5.5698
## X1 0.1697 0.1512 1.1225 0.2626 -0.1279 0.4673
## X2 0.2000 0.1531 1.3065 0.1924 -0.1013 0.5012
## guilt -0.0833 0.0374 -2.2308 0.0264 -0.1569 -0.0098
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0996 0.0099 1.1495 1.4887 2.0000 297.0000 0.2273
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8384 0.1078 44.9009 0.0000 4.6263 5.0504
## X1 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## ***********************************************************************
## 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 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0099 1.4887 2.0000 297.0000 0.2273
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.1697 0.1512 1.1225 0.2626 -0.1279 0.4673
## X2 0.2000 0.1531 1.3065 0.1924 -0.1013 0.5012
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0066 1.0094 2.0000 296.0000 0.3657
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> guilt -> punish_post
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0181 0.0235 -0.0749 0.0201
## X2 0.0607 0.0406 -0.0026 0.1529
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0181 0.0229 -0.7911 0.4289
## X2 0.0607 0.0346 1.7540 0.0794
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: condition -> SFC -> punish_post
##
## ********************* 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 : punish_post
## X : condition_1
## M : SFC
##
## Sample size: 300
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## condition_1 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
## 0.1406 0.0198 2.1959 2.9966 2.0000 297.0000 0.0515
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.9899 0.1489 20.0755 0.0000 2.6968 3.2830
## X1 0.4701 0.2101 2.2376 0.0260 0.0566 0.8836
## X2 0.4160 0.2096 1.9851 0.0480 0.0036 0.8285
##
## ***********************************************************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2921 0.0853 1.0656 9.2067 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.2413 0.1593 26.6287 0.0000 3.9279 4.5548
## X1 0.0577 0.1476 0.3912 0.6959 -0.2327 0.3482
## X2 0.1775 0.1470 1.2081 0.2280 -0.1117 0.4668
## SFC 0.1997 0.0404 4.9404 0.0000 0.1201 0.2792
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punish_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0996 0.0099 1.1495 1.4887 2.0000 297.0000 0.2273
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8384 0.1078 44.9009 0.0000 4.6263 5.0504
## X1 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## ***********************************************************************
## 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 0.1516 0.1520 0.9974 0.3194 -0.1475 0.4508
## X2 0.2606 0.1516 1.7188 0.0867 -0.0378 0.5590
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0099 1.4887 2.0000 297.0000 0.2273
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.0577 0.1476 0.3912 0.6959 -0.2327 0.3482
## X2 0.1775 0.1470 1.2081 0.2280 -0.1117 0.4668
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0047 0.7644 2.0000 296.0000 0.4665
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> SFC -> punish_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0939 0.0486 0.0095 0.2012
## X2 0.0831 0.0474 -0.0009 0.1854
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0939 0.0468 2.0045 0.0450
## X2 0.0831 0.0459 1.8104 0.0702
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000