##
## ********************* 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 = blame ~ ses_origin_, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.2807 -0.2807 0.1976 0.9585 1.7193
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.2807 0.1495 28.63 < 2e-16 ***
## ses_origin_ 0.7608 0.1178 6.46 1.29e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.178 on 155 degrees of freedom
## Multiple R-squared: 0.2121, Adjusted R-squared: 0.207
## F-statistic: 41.73 on 1 and 155 DF, p-value: 1.286e-09Mediation analysis: ses_origin_ -> surprise -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5220 0.2725 1.2974 19.1007 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.9035 0.1839 21.2303 0.0000 3.5403 4.2668
## X1 1.0667 0.2578 4.1381 0.0001 0.5575 1.5760
## X2 1.2443 0.2678 4.6461 0.0000 0.7152 1.7734
## surprise 0.1088 0.0569 1.9122 0.0577 -0.0036 0.2212
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.0667 0.2578 4.1381 0.0001 0.5575 1.5760
## X2 1.2443 0.2678 4.6461 0.0000 0.7152 1.7734
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1133 11.9158 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2583 0.1367 0.0186 0.5597
## X2 0.2691 0.1493 0.0187 0.6058
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2583 0.1404 1.8401 0.0657
## X2 0.2691 0.1462 1.8406 0.0657
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6471 0.4188 1.0365 36.7472 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.8078 0.2995 19.3886 0.0000 5.2161 6.3996
## X1 0.3918 0.2423 1.6170 0.1079 -0.0869 0.8705
## X2 0.2396 0.2813 0.8518 0.3957 -0.3161 0.7953
## sympathy -0.3660 0.0558 -6.5644 0.0000 -0.4761 -0.2558
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.3918 0.2423 1.6170 0.1079 -0.0869 0.8705
## X2 0.2396 0.2813 0.8518 0.3957 -0.3161 0.7953
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0105 1.3874 2.0000 153.0000 0.2528
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> sympathy -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.9333 0.1809 0.6040 1.3173
## X2 1.2738 0.1987 0.8960 1.6752
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.9333 0.1767 5.2804 0.0000
## X2 1.2738 0.2226 5.7237 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5426 0.2944 1.2583 21.2766 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8555 0.3091 15.7076 0.0000 4.2448 5.4662
## X1 1.2220 0.2191 5.5776 0.0000 0.7891 1.6548
## X2 1.2524 0.2416 5.1845 0.0000 0.7751 1.7296
## character -0.2431 0.0833 -2.9187 0.0040 -0.4077 -0.0786
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.2220 0.2191 5.5776 0.0000 0.7891 1.6548
## X2 1.2524 0.2416 5.1845 0.0000 0.7751 1.7296
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1758 19.0573 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> character -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1031 0.0604 0.0055 0.2394
## X2 0.2610 0.1070 0.0694 0.4851
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1031 0.0643 1.6031 0.1089
## X2 0.2610 0.1054 2.4764 0.0133
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7024 0.4934 0.9034 49.6676 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.0206 0.2767 7.3027 0.0000 1.4740 2.5672
## X1 0.9718 0.1879 5.1724 0.0000 0.6006 1.3430
## X2 0.9093 0.2030 4.4783 0.0000 0.5081 1.3104
## wrongness 0.4998 0.0589 8.4832 0.0000 0.3834 0.6161
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9718 0.1879 5.1724 0.0000 0.6006 1.3430
## X2 0.9093 0.2030 4.4783 0.0000 0.5081 1.3104
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1017 15.3617 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> wrongness -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3533 0.1571 0.0746 0.6896
## X2 0.6042 0.1791 0.2859 0.9812
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3533 0.1328 2.6602 0.0078
## X2 0.6042 0.1490 4.0547 0.0001
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> justification -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7934 0.6295 0.6607 86.6495 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.4060 0.1561 34.6407 0.0000 5.0977 5.7143
## X1 0.5374 0.1690 3.1801 0.0018 0.2036 0.8713
## X2 0.3571 0.1873 1.9065 0.0585 -0.0129 0.7272
## justification -0.5596 0.0450 -12.4342 0.0000 -0.6485 -0.4707
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5374 0.1690 3.1801 0.0018 0.2036 0.8713
## X2 0.3571 0.1873 1.9065 0.0585 -0.0129 0.7272
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0245 5.0567 2.0000 153.0000 0.0075
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justification -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.7877 0.2266 0.3751 1.2600
## X2 1.1563 0.2107 0.7711 1.5945
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.7877 0.1698 4.6400 0.0000
## X2 1.1563 0.1881 6.1488 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_ -> reasons -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7585 0.5753 0.7573 69.0978 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.8147 0.2024 28.7254 0.0000 5.4148 6.2146
## X1 0.0647 0.2047 0.3161 0.7523 -0.3397 0.4691
## X2 0.0905 0.2187 0.4136 0.6797 -0.3417 0.5226
## reasons -0.5119 0.0477 -10.7418 0.0000 -0.6060 -0.4177
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.0647 0.2047 0.3161 0.7523 -0.3397 0.4691
## X2 0.0905 0.2187 0.4136 0.6797 -0.3417 0.5226
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0005 0.0867 2.0000 153.0000 0.9170
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> reasons -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 1.2604 0.2352 0.8394 1.7490
## X2 1.4229 0.2262 1.0141 1.8888
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 1.2604 0.1872 6.7341 0.0000
## X2 1.4229 0.2011 7.0750 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> justreasons -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.8058 0.6493 0.6253 94.4370 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.8337 0.1737 33.5843 0.0000 5.4905 6.1769
## X1 0.1467 0.1769 0.8293 0.4082 -0.2028 0.4963
## X2 0.0378 0.1941 0.1945 0.8460 -0.3457 0.4213
## justreasons -0.6090 0.0464 -13.1154 0.0000 -0.7007 -0.5172
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.1467 0.1769 0.8293 0.4082 -0.2028 0.4963
## X2 0.0378 0.1941 0.1945 0.8460 -0.3457 0.4213
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0021 0.4476 2.0000 153.0000 0.6400
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justreasons -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 1.1784 0.2562 0.7228 1.7226
## X2 1.4756 0.2387 1.0456 1.9755
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 1.1784 0.1849 6.3743 0.0000
## X2 1.4756 0.2019 7.3080 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> guilt -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5236 0.2742 1.2943 19.2647 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.5763 0.2949 15.5158 0.0000 3.9936 5.1590
## X1 1.2330 0.2240 5.5036 0.0000 0.7904 1.6756
## X2 1.3547 0.2410 5.6221 0.0000 0.8786 1.8307
## guilt -0.1329 0.0663 -2.0058 0.0466 -0.2639 -0.0020
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.2330 0.2240 5.5036 0.0000 0.7904 1.6756
## X2 1.3547 0.2410 5.6221 0.0000 0.8786 1.8307
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1910 20.1357 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> guilt -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0921 0.0559 0.0071 0.2221
## X2 0.1587 0.0824 0.0162 0.3349
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0921 0.0606 1.5185 0.1289
## X2 0.1587 0.0892 1.7800 0.0751
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5052 0.2553 1.3280 17.4818 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0378 0.2618 15.4216 0.0000 3.5206 4.5551
## X1 1.3089 0.2367 5.5289 0.0000 0.8412 1.7767
## X2 1.5086 0.2318 6.5071 0.0000 1.0506 1.9666
## emo_sup 0.0142 0.0720 0.1969 0.8442 -0.1281 0.1565
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.3089 0.2367 5.5289 0.0000 0.8412 1.7767
## X2 1.5086 0.2318 6.5071 0.0000 1.0506 1.9666
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.2381 24.4556 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> emo_sup -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0161 0.0772 -0.1439 0.1650
## X2 0.0048 0.0283 -0.0640 0.0583
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0161 0.0839 0.1922 0.8476
## X2 0.0048 0.0310 0.1560 0.8760
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5490 0.3014 1.2458 22.0028 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.7384 0.2596 18.2557 0.0000 4.2256 5.2511
## X1 1.0520 0.2316 4.5424 0.0000 0.5945 1.5095
## X2 1.3982 0.2262 6.1818 0.0000 0.9514 1.8451
## abuse -0.1934 0.0607 -3.1846 0.0018 -0.3134 -0.0734
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.0520 0.2316 4.5424 0.0000 0.5945 1.5095
## X2 1.3982 0.2262 6.1818 0.0000 0.9514 1.8451
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1850 20.2635 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> abuse -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2731 0.1054 0.0978 0.5088
## X2 0.1152 0.0670 0.0055 0.2669
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2731 0.1034 2.6398 0.0083
## X2 0.1152 0.0701 1.6429 0.1004
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6106 0.3729 1.1183 30.3241 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0236 0.2463 12.2780 0.0000 2.5371 3.5101
## X1 0.9845 0.2135 4.6111 0.0000 0.5627 1.4063
## X2 1.2413 0.2175 5.7061 0.0000 0.8116 1.6711
## SFC 0.3300 0.0616 5.3608 0.0000 0.2084 0.4517
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.9845 0.2135 4.6111 0.0000 0.5627 1.4063
## X2 1.2413 0.2175 5.7061 0.0000 0.8116 1.6711
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1469 17.9167 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SFC -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3406 0.1124 0.1483 0.5888
## X2 0.2721 0.1205 0.0672 0.5418
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3406 0.1098 3.1015 0.0019
## X2 0.2721 0.1059 2.5687 0.0102
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5990 0.3588 1.1434 28.5401 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2329 0.2265 14.2730 0.0000 2.7854 3.6804
## X1 1.0857 0.2116 5.1296 0.0000 0.6675 1.5038
## X2 1.1651 0.2251 5.1765 0.0000 0.7204 1.6097
## SE 0.3343 0.0672 4.9750 0.0000 0.2015 0.4670
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.0857 0.2116 5.1296 0.0000 0.6675 1.5038
## X2 1.1651 0.2251 5.1765 0.0000 0.7204 1.6097
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1444 17.2285 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SE -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2394 0.0943 0.0762 0.4426
## X2 0.3483 0.1201 0.1435 0.6098
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2394 0.0971 2.4668 0.0136
## X2 0.3483 0.1120 3.1089 0.0019
##
## ******************** 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 -> blame
##
## ********************* 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
## 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3284 17.4645 3.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0811 0.3382 12.0676 0.0000 3.4130 4.7492
## X1 1.3243 0.2367 5.5941 0.0000 0.8566 1.7920
## X2 1.5129 0.2380 6.3553 0.0000 1.0426 1.9832
## upbringing -0.0006 0.0686 -0.0090 0.9929 -0.1361 0.1349
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 1.3243 0.2367 5.5941 0.0000 0.8566 1.7920
## X2 1.5129 0.2380 6.3553 0.0000 1.0426 1.9832
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.2276 23.3776 2.0000 153.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> upbringing -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0007 0.0777 -0.1430 0.1645
## X2 0.0005 0.0568 -0.1124 0.1190
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0007 0.0838 0.0088 0.9930
## X2 0.0005 0.0621 0.0086 0.9932
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediators in parallel:
(Not emo_sup, 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 : blame
## X : ses_origin_
## M1 : surprise
## M2 : sympathy
## M3 : character
## M4 : wrongness
## M5 : justreasons
## M6 : guilt
## M7 : abuse
## M8 : SFC
## M9 : 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: 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: 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: 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: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.8445 0.7132 0.5396 32.7872 11.0000 145.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.6834 0.4899 9.5595 0.0000 3.7151 5.6517
## X1 -0.1781 0.2012 -0.8853 0.3775 -0.5757 0.2195
## X2 -0.3184 0.2242 -1.4203 0.1577 -0.7615 0.1247
## surprise 0.0311 0.0399 0.7789 0.4373 -0.0478 0.1099
## sympathy -0.1271 0.0503 -2.5275 0.0126 -0.2265 -0.0277
## character 0.1217 0.0652 1.8680 0.0638 -0.0071 0.2505
## wrongness 0.1274 0.0629 2.0246 0.0447 0.0030 0.2519
## justreasons -0.4298 0.0637 -6.7502 0.0000 -0.5557 -0.3040
## guilt -0.0137 0.0467 -0.2928 0.7701 -0.1060 0.0786
## abuse -0.0553 0.0430 -1.2864 0.2004 -0.1402 0.0296
## SFC 0.0242 0.0525 0.4603 0.6460 -0.0796 0.1280
## SE 0.1713 0.0538 3.1818 0.0018 0.0649 0.2777
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5051 0.2551 1.3198 26.3679 2.0000 154.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0784 0.1609 25.3531 0.0000 3.7606 4.3962
## X1 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## ***********************************************************************
## 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 1.3251 0.2214 5.9842 0.0000 0.8876 1.7625
## X2 1.5134 0.2298 6.5855 0.0000 1.0594 1.9674
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2551 26.3679 2.0000 154.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.1781 0.2012 -0.8853 0.3775 -0.5757 0.2195
## X2 -0.3184 0.2242 -1.4203 0.1577 -0.7615 0.1247
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0041 1.0302 2.0000 145.0000 0.3595
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0738 0.0944 -0.1136 0.2640
## X2 0.0769 0.1004 -0.1172 0.2821
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0738 0.0960 0.7684 0.4422
## X2 0.0769 0.1000 0.7685 0.4422
##
## ses_origin_ -> sympathy -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3241 0.1386 0.0622 0.6049
## X2 0.4424 0.1825 0.0868 0.8045
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3241 0.1340 2.4193 0.0155
## X2 0.4424 0.1796 2.4632 0.0138
##
## ses_origin_ -> character -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0516 0.0360 -0.1276 0.0150
## X2 -0.1307 0.0796 -0.2877 0.0275
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0516 0.0400 -1.2916 0.1965
## X2 -0.1307 0.0761 -1.7170 0.0860
##
## ses_origin_ -> wrongness -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0901 0.0740 -0.0173 0.2659
## X2 0.1541 0.1122 -0.0329 0.4053
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0901 0.0570 1.5806 0.1140
## X2 0.1541 0.0846 1.8211 0.0686
##
## ses_origin_ -> justreasons -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.8317 0.1968 0.4923 1.2572
## X2 1.0415 0.1910 0.6910 1.4326
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.8317 0.1685 4.9359 0.0000
## X2 1.0415 0.1950 5.3403 0.0000
##
## ses_origin_ -> guilt -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0095 0.0314 -0.0567 0.0720
## X2 0.0163 0.0522 -0.0996 0.1118
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0095 0.0348 0.2718 0.7858
## X2 0.0163 0.0574 0.2847 0.7759
##
## ses_origin_ -> abuse -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0780 0.0629 -0.0414 0.2092
## X2 0.0329 0.0307 -0.0204 0.1012
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0780 0.0639 1.2218 0.2218
## X2 0.0329 0.0329 0.9993 0.3176
##
## ses_origin_ -> SFC -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0249 0.0580 -0.0938 0.1392
## X2 0.0199 0.0486 -0.0787 0.1215
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0249 0.0563 0.4427 0.6580
## X2 0.0199 0.0462 0.4317 0.6659
##
## ses_origin_ -> SE -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1227 0.0614 0.0215 0.2590
## X2 0.1785 0.0807 0.0405 0.3530
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1227 0.0588 2.0867 0.0369
## X2 0.1785 0.0726 2.4590 0.0139
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000