##
## ********************* 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 = blame_post ~ condition_1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.3814 -0.3814 0.6186 0.6703 0.7220
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.27795 0.09583 55.074 <2e-16 ***
## condition_1 0.05170 0.07394 0.699 0.485
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.046 on 298 degrees of freedom
## Multiple R-squared: 0.001638, Adjusted R-squared: -0.001712
## F-statistic: 0.489 on 1 and 298 DF, p-value: 0.4849Mediation analysis: condition -> character -> blame_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 : blame_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: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2825 0.0798 1.0145 8.5582 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.8631 0.1497 39.1651 0.0000 5.5685 6.1577
## X1 -0.1162 0.1430 -0.8125 0.4172 -0.3975 0.1652
## X2 -0.0126 0.1444 -0.0876 0.9303 -0.2968 0.2715
## character -0.2294 0.0469 -4.8948 0.0000 -0.3216 -0.1371
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0730 0.0053 1.0929 0.7962 2.0000 297.0000 0.4520
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.3232 0.1051 50.6645 0.0000 5.1165 5.5300
## X1 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## ***********************************************************************
## 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 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0053 0.7962 2.0000 297.0000 0.4520
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.1162 0.1430 -0.8125 0.4172 -0.3975 0.1652
## X2 -0.0126 0.1444 -0.0876 0.9303 -0.2968 0.2715
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0025 0.3996 2.0000 296.0000 0.6709
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> character -> blame_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0329 0.0430 -0.0460 0.1250
## X2 0.1152 0.0520 0.0300 0.2341
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0329 0.0419 0.7850 0.4324
## X2 0.1152 0.0475 2.4230 0.0154
##
## ******************** 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 -> blame_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 : blame_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: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5015 0.2515 0.8252 33.1524 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.5254 0.3956 3.8561 0.0001 0.7469 2.3040
## X1 -0.1815 0.1292 -1.4049 0.1611 -0.4357 0.0727
## X2 -0.0179 0.1291 -0.1384 0.8900 -0.2718 0.2361
## wrongness 0.6811 0.0690 9.8665 0.0000 0.5453 0.8170
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0730 0.0053 1.0929 0.7962 2.0000 297.0000 0.4520
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.3232 0.1051 50.6645 0.0000 5.1165 5.5300
## X1 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## ***********************************************************************
## 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 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0053 0.7962 2.0000 297.0000 0.4520
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.1815 0.1292 -1.4049 0.1611 -0.4357 0.0727
## X2 -0.0179 0.1291 -0.1384 0.8900 -0.2718 0.2361
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0061 1.2090 2.0000 296.0000 0.3000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> wrongness -> blame_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0982 0.0733 -0.0403 0.2495
## X2 0.1204 0.0749 -0.0363 0.2607
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0982 0.0748 1.3138 0.1889
## X2 0.1204 0.0749 1.6064 0.1082
##
## ******************** 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 -> blame_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 : blame_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: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5623 0.3162 0.7539 45.6240 3.0000 296.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.6435 0.0915 61.6594 0.0000 5.4634 5.8237
## X1 -0.0666 0.1231 -0.5411 0.5888 -0.3089 0.1757
## X2 -0.0019 0.1231 -0.0158 0.9874 -0.2443 0.2404
## justification -0.4955 0.0427 -11.6001 0.0000 -0.5795 -0.4114
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0730 0.0053 1.0929 0.7962 2.0000 297.0000 0.4520
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.3232 0.1051 50.6645 0.0000 5.1165 5.5300
## X1 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## ***********************************************************************
## 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 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0053 0.7962 2.0000 297.0000 0.4520
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.0666 0.1231 -0.5411 0.5888 -0.3089 0.1757
## X2 -0.0019 0.1231 -0.0158 0.9874 -0.2443 0.2404
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0009 0.1900 2.0000 296.0000 0.8270
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> justification -> blame_post
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0166 0.0889 -0.1891 0.1644
## X2 0.1045 0.0767 -0.0512 0.2503
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0166 0.0832 -0.1998 0.8417
## X2 0.1045 0.0834 1.2517 0.2107
##
## ******************** 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 -> guilt -> blame_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 : blame_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: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0751 0.0056 1.0962 0.5600 3.0000 296.0000 0.6418
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.2758 0.1883 28.0150 0.0000 4.9051 5.6464
## X1 -0.0857 0.1487 -0.5762 0.5649 -0.3782 0.2069
## X2 0.1106 0.1505 0.7353 0.4628 -0.1855 0.4068
## guilt 0.0112 0.0367 0.3040 0.7613 -0.0611 0.0834
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0730 0.0053 1.0929 0.7962 2.0000 297.0000 0.4520
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.3232 0.1051 50.6645 0.0000 5.1165 5.5300
## X1 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## ***********************************************************************
## 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 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0053 0.7962 2.0000 297.0000 0.4520
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.0857 0.1487 -0.5762 0.5649 -0.3782 0.2069
## X2 0.1106 0.1505 0.7353 0.4628 -0.1855 0.4068
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0056 0.8400 2.0000 296.0000 0.4327
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> guilt -> blame_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0024 0.0151 -0.0266 0.0390
## X2 -0.0081 0.0362 -0.0880 0.0617
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0024 0.0120 0.2018 0.8401
## X2 -0.0081 0.0282 -0.2882 0.7732
##
## ******************** 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 -> blame_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 : blame_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: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1661 0.0276 1.0720 2.7996 3.0000 296.0000 0.0403
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0077 0.1598 31.3451 0.0000 4.6933 5.3221
## X1 -0.1328 0.1480 -0.8974 0.3702 -0.4242 0.1585
## X2 0.0586 0.1474 0.3976 0.6912 -0.2315 0.3487
## SFC 0.1055 0.0405 2.6030 0.0097 0.0257 0.1853
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame_post
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0730 0.0053 1.0929 0.7962 2.0000 297.0000 0.4520
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.3232 0.1051 50.6645 0.0000 5.1165 5.5300
## X1 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## ***********************************************************************
## 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 -0.0832 0.1482 -0.5616 0.5748 -0.3749 0.2085
## X2 0.1025 0.1479 0.6933 0.4886 -0.1885 0.3935
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0053 0.7962 2.0000 297.0000 0.4520
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.1328 0.1480 -0.8974 0.3702 -0.4242 0.1585
## X2 0.0586 0.1474 0.3976 0.6912 -0.2315 0.3487
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0059 0.8987 2.0000 296.0000 0.4082
##
## ----------
##
## Relative indirect effects of X on Y:
##
## condition_1 -> SFC -> blame_post
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0496 0.0328 -0.0004 0.1237
## X2 0.0439 0.0311 -0.0035 0.1163
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0496 0.0305 1.6291 0.1033
## X2 0.0439 0.0291 1.5096 0.1311
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000