##
## ********************* 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
## -5.7048 -0.1143 0.2952 0.5905 0.8857
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.1143 0.1387 36.883 < 2e-16 ***
## ses_origin_ 0.2952 0.1052 2.805 0.00566 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.109 on 157 degrees of freedom
## Multiple R-squared: 0.04773, Adjusted R-squared: 0.04167
## F-statistic: 7.869 on 1 and 157 DF, p-value: 0.005664Mediation 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: surprise
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3369 0.1135 2.9522 9.9873 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0556 0.2338 13.0682 0.0000 2.5937 3.5174
## X1 1.5069 0.3408 4.4212 0.0000 0.8337 2.1802
## X2 0.5234 0.3263 1.6041 0.1107 -0.1211 1.1679
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3376 0.1140 1.1581 6.6480 3.0000 155.0000 0.0003
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.5574 0.2120 21.5017 0.0000 4.1387 4.9761
## X1 0.3097 0.2265 1.3677 0.1734 -0.1376 0.7571
## X2 0.5124 0.2060 2.4868 0.0140 0.1054 0.9194
## surprise 0.1570 0.0501 3.1305 0.0021 0.0579 0.2560
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.3097 0.2265 1.3677 0.1734 -0.1376 0.7571
## X2 0.5124 0.2060 2.4868 0.0140 0.1054 0.9194
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0355 3.1015 2.0000 155.0000 0.0478
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2366 0.1179 0.0505 0.5062
## X2 0.0822 0.0681 -0.0247 0.2403
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2366 0.0942 2.5124 0.0120
## X2 0.0822 0.0598 1.3732 0.1697
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5974 0.3568 2.2091 43.2773 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6852 0.2023 18.2201 0.0000 3.2857 4.0847
## X1 -1.5602 0.2948 -5.2916 0.0000 -2.1426 -0.9778
## X2 -2.6150 0.2822 -9.2649 0.0000 -3.1725 -2.0575
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3648 0.1331 1.1332 7.9294 3.0000 155.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.8112 0.2562 22.6817 0.0000 5.3051 6.3173
## X1 0.2185 0.2293 0.9529 0.3421 -0.2345 0.6716
## X2 0.0452 0.2517 0.1795 0.8578 -0.4520 0.5424
## sympathy -0.2101 0.0573 -3.6635 0.0003 -0.3234 -0.0968
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.2185 0.2293 0.9529 0.3421 -0.2345 0.6716
## X2 0.0452 0.2517 0.1795 0.8578 -0.4520 0.5424
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0064 0.5709 2.0000 155.0000 0.5662
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> sympathy -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3278 0.1155 0.1330 0.5834
## X2 0.5494 0.1677 0.2496 0.9091
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3278 0.1101 2.9764 0.0029
## X2 0.5494 0.1621 3.3898 0.0007
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: ses_origin_ -> character -> 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: character
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2920 0.0852 1.2394 7.2683 2.0000 156.0000 0.0010
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.8333 0.1515 18.7022 0.0000 2.5341 3.1326
## X1 -0.5833 0.2208 -2.6414 0.0091 -1.0196 -0.1471
## X2 -0.7807 0.2114 -3.6928 0.0003 -1.1983 -0.3631
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2782 0.0774 1.2060 4.3331 3.0000 155.0000 0.0058
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.4409 0.2691 20.2202 0.0000 4.9094 5.9725
## X1 0.4631 0.2227 2.0800 0.0392 0.0233 0.9030
## X2 0.4833 0.2175 2.2222 0.0277 0.0537 0.9128
## character -0.1426 0.0790 -1.8050 0.0730 -0.2986 0.0135
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.4631 0.2227 2.0800 0.0392 0.0233 0.9030
## X2 0.4833 0.2175 2.2222 0.0277 0.0537 0.9128
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0364 3.0549 2.0000 155.0000 0.0500
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> character -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0832 0.0737 -0.0338 0.2547
## X2 0.1113 0.0903 -0.0469 0.3125
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0832 0.0585 1.4224 0.1549
## X2 0.1113 0.0706 1.5757 0.1151
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: wrongness
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.0976 0.0095 1.1873 0.7503 2.0000 156.0000 0.4739
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.2037 0.1483 35.0943 0.0000 4.9108 5.4966
## X1 0.1088 0.2161 0.5033 0.6154 -0.3182 0.5358
## X2 0.2524 0.2069 1.2200 0.2243 -0.1563 0.6612
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5024 0.2524 0.9772 17.4470 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.6370 0.4012 6.5730 0.0000 1.8445 3.4296
## X1 0.4961 0.1963 2.5280 0.0125 0.1084 0.8838
## X2 0.4781 0.1886 2.5349 0.0122 0.1055 0.8507
## wrongness 0.4612 0.0726 6.3497 0.0000 0.3177 0.6047
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.4961 0.1963 2.5280 0.0125 0.1084 0.8838
## X2 0.4781 0.1886 2.5349 0.0122 0.1055 0.8507
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0414 4.2928 2.0000 155.0000 0.0153
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> wrongness -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0502 0.1132 -0.1326 0.3200
## X2 0.1164 0.1109 -0.0526 0.3805
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0502 0.1012 0.4957 0.6201
## X2 0.1164 0.0983 1.1840 0.2364
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: justification
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1662 0.0276 1.7077 2.2167 2.0000 156.0000 0.1124
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.6296 0.1778 3.5406 0.0005 0.2784 0.9809
## X1 0.3287 0.2592 1.2680 0.2067 -0.1834 0.8408
## X2 -0.2086 0.2482 -0.8405 0.4019 -0.6988 0.2816
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4211 0.1773 1.0754 11.1349 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.2267 0.1467 35.6339 0.0000 4.9370 5.5164
## X1 0.6453 0.2068 3.1209 0.0022 0.2369 1.0538
## X2 0.5317 0.1974 2.6940 0.0078 0.1418 0.9216
## justification -0.3012 0.0635 -4.7413 0.0000 -0.4267 -0.1757
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6453 0.2068 3.1209 0.0022 0.2369 1.0538
## X2 0.5317 0.1974 2.6940 0.0078 0.1418 0.9216
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0615 5.7949 2.0000 155.0000 0.0037
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justification -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0990 0.0846 -0.2585 0.0868
## X2 0.0628 0.0700 -0.0640 0.2127
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0990 0.0825 -1.2003 0.2300
## X2 0.0628 0.0775 0.8103 0.4178
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: reasons
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1342 0.0180 1.3506 1.4314 2.0000 156.0000 0.2421
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.5741 0.1582 3.6299 0.0004 0.2617 0.8865
## X1 0.3009 0.2305 1.3053 0.1937 -0.1545 0.7563
## X2 -0.0653 0.2207 -0.2959 0.7677 -0.5012 0.3706
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3661 0.1340 1.1320 7.9945 3.0000 155.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.1922 0.1508 34.4371 0.0000 4.8944 5.4901
## X1 0.6277 0.2122 2.9577 0.0036 0.2085 1.0468
## X2 0.5769 0.2021 2.8545 0.0049 0.1777 0.9761
## reasons -0.2704 0.0733 -3.6885 0.0003 -0.4151 -0.1256
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6277 0.2122 2.9577 0.0036 0.2085 1.0468
## X2 0.5769 0.2021 2.8545 0.0049 0.1777 0.9761
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0636 5.6873 2.0000 155.0000 0.0041
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> reasons -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0814 0.0680 -0.2159 0.0565
## X2 0.0177 0.0567 -0.0755 0.1501
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0814 0.0682 -1.1922 0.2332
## X2 0.0177 0.0620 0.2847 0.7759
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: justreasons
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1765 0.0311 1.0948 2.5075 2.0000 156.0000 0.0847
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.6019 0.1424 4.2269 0.0000 0.3206 0.8831
## X1 0.3148 0.2076 1.5167 0.1314 -0.0952 0.7248
## X2 -0.1369 0.1987 -0.6892 0.4917 -0.5294 0.2555
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4405 0.1940 1.0535 12.4372 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.2788 0.1475 35.7986 0.0000 4.9875 5.5701
## X1 0.6728 0.2051 3.2800 0.0013 0.2676 1.0779
## X2 0.5395 0.1952 2.7638 0.0064 0.1539 0.9252
## justreasons -0.4017 0.0785 -5.1147 0.0000 -0.5569 -0.2466
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6728 0.2051 3.2800 0.0013 0.2676 1.0779
## X2 0.5395 0.1952 2.7638 0.0064 0.1539 0.9252
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0655 6.2960 2.0000 155.0000 0.0024
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> justreasons -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.1265 0.0901 -0.3012 0.0570
## X2 0.0550 0.0753 -0.0825 0.2180
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.1265 0.0885 -1.4292 0.1529
## X2 0.0550 0.0820 0.6705 0.5025
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: guilt
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2012 0.0405 2.0157 3.2896 2.0000 156.0000 0.0399
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2037 0.1932 16.5820 0.0000 2.8221 3.5853
## X1 -0.4745 0.2816 -1.6849 0.0940 -1.0309 0.0818
## X2 -0.6774 0.2696 -2.5125 0.0130 -1.2100 -0.1448
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3189 0.1017 1.1742 5.8492 3.0000 155.0000 0.0008
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.5747 0.2451 22.7453 0.0000 5.0905 6.0588
## X1 0.4667 0.2169 2.1514 0.0330 0.0382 0.8951
## X2 0.4809 0.2099 2.2909 0.0233 0.0662 0.8955
## guilt -0.1678 0.0611 -2.7463 0.0067 -0.2885 -0.0471
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.4667 0.2169 2.1514 0.0330 0.0382 0.8951
## X2 0.4809 0.2099 2.2909 0.0233 0.0662 0.8955
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0381 3.2902 2.0000 155.0000 0.0399
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> guilt -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0796 0.0671 -0.0106 0.2438
## X2 0.1137 0.0771 -0.0001 0.2951
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0796 0.0581 1.3716 0.1702
## X2 0.1137 0.0635 1.7903 0.0734
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: emo_sup
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3868 0.1496 1.9137 13.7253 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 2.4259 0.1883 12.8866 0.0000 2.0541 2.7978
## X1 1.4074 0.2744 5.1286 0.0000 0.8653 1.9495
## X2 0.9074 0.2627 3.4541 0.0007 0.3885 1.4263
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2426 0.0588 1.2302 3.2301 3.0000 155.0000 0.0241
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0954 0.2169 23.4952 0.0000 4.6670 5.5238
## X1 0.5802 0.2379 2.4392 0.0158 0.1103 1.0500
## X2 0.6164 0.2185 2.8205 0.0054 0.1847 1.0481
## emo_sup -0.0241 0.0642 -0.3749 0.7082 -0.1509 0.1027
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5802 0.2379 2.4392 0.0158 0.1103 1.0500
## X2 0.6164 0.2185 2.8205 0.0054 0.1847 1.0481
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0555 4.5713 2.0000 155.0000 0.0118
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> emo_sup -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0339 0.1031 -0.2519 0.1520
## X2 -0.0218 0.0696 -0.1790 0.0977
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0339 0.0923 -0.3671 0.7136
## X2 -0.0218 0.0610 -0.3582 0.7202
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: abuse
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3356 0.1126 2.0789 9.9013 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.5556 0.1962 18.1210 0.0000 3.1680 3.9431
## X1 -1.2222 0.2860 -4.2731 0.0000 -1.7872 -0.6572
## X2 -0.8713 0.2738 -3.1823 0.0018 -1.4122 -0.3305
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2454 0.0602 1.2284 3.3098 3.0000 155.0000 0.0217
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.1694 0.2658 19.4508 0.0000 4.6444 5.6944
## X1 0.5008 0.2324 2.1551 0.0327 0.0418 0.9598
## X2 0.5621 0.2172 2.5879 0.0106 0.1330 0.9912
## abuse -0.0372 0.0615 -0.6050 0.5461 -0.1588 0.0843
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5008 0.2324 2.1551 0.0327 0.0418 0.9598
## X2 0.5621 0.2172 2.5879 0.0106 0.1330 0.9912
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0458 3.7741 2.0000 155.0000 0.0251
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> abuse -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0455 0.0878 -0.1379 0.2150
## X2 0.0324 0.0631 -0.1013 0.1527
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0455 0.0780 0.5836 0.5595
## X2 0.0324 0.0571 0.5679 0.5701
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: SFC
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1162 0.0135 1.7072 1.0680 2.0000 156.0000 0.3462
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0000 0.1778 22.4968 0.0000 3.6488 4.3512
## X1 -0.0000 0.2592 -0.0000 1.0000 -0.5120 0.5120
## X2 0.3158 0.2481 1.2727 0.2050 -0.1743 0.8059
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4119 0.1697 1.0853 10.5583 3.0000 155.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8710 0.2921 13.2538 0.0000 3.2941 4.4480
## X1 0.5463 0.2067 2.6434 0.0091 0.1381 0.9545
## X2 0.5025 0.1989 2.5268 0.0125 0.1097 0.8953
## SFC 0.2915 0.0638 4.5662 0.0000 0.1654 0.4176
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5463 0.2067 2.6434 0.0091 0.1381 0.9545
## X2 0.5025 0.1989 2.5268 0.0125 0.1097 0.8953
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0482 4.4946 2.0000 155.0000 0.0127
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SFC -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0000 0.0755 -0.1499 0.1569
## X2 0.0921 0.0817 -0.0555 0.2774
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0000 0.0773 -0.0000 1.0000
## X2 0.0921 0.0767 1.1996 0.2303
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2626 0.0689 1.6061 5.7762 2.0000 156.0000 0.0038
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2778 0.1725 19.0059 0.0000 2.9371 3.6184
## X1 0.2222 0.2514 0.8839 0.3781 -0.2744 0.7188
## X2 0.7924 0.2407 3.2925 0.0012 0.3170 1.2678
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3654 0.1335 1.1326 7.9609 3.0000 155.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.2270 0.2637 16.0292 0.0000 3.7061 4.7479
## X1 0.4914 0.2116 2.3217 0.0216 0.0733 0.9095
## X2 0.3987 0.2090 1.9077 0.0583 -0.0141 0.8116
## SE 0.2471 0.0672 3.6756 0.0003 0.1143 0.3799
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.4914 0.2116 2.3217 0.0216 0.0733 0.9095
## X2 0.3987 0.2090 1.9077 0.0583 -0.0141 0.8116
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0345 3.0814 2.0000 155.0000 0.0487
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> SE -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0549 0.0763 -0.0711 0.2308
## X2 0.1958 0.0939 0.0466 0.4098
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0549 0.0661 0.8309 0.4061
## X2 0.1958 0.0815 2.4036 0.0162
##
## ******************** 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: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: upbringing
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3311 0.1096 2.0941 9.6059 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0741 0.1969 20.6882 0.0000 3.6851 4.4631
## X1 -1.2407 0.2871 -4.3221 0.0000 -1.8078 -0.6737
## X2 -0.7583 0.2748 -2.7593 0.0065 -1.3011 -0.2155
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2567 0.0659 1.2210 3.6435 3.0000 155.0000 0.0141
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.3220 0.2909 18.2922 0.0000 4.7473 5.8967
## X1 0.4595 0.2320 1.9810 0.0494 0.0013 0.9177
## X2 0.5415 0.2149 2.5198 0.0128 0.1170 0.9660
## upbringing -0.0699 0.0611 -1.1441 0.2544 -0.1907 0.0508
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.4595 0.2320 1.9810 0.0494 0.0013 0.9177
## X2 0.5415 0.2149 2.5198 0.0128 0.1170 0.9660
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0419 3.4752 2.0000 155.0000 0.0334
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> upbringing -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0868 0.0573 -0.0210 0.2059
## X2 0.0530 0.0381 -0.0119 0.1388
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0868 0.0804 1.0793 0.2804
## X2 0.0530 0.0529 1.0022 0.3163
##
## ******************** 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:
##
## ********************* 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 : SE
##
## Sample size: 159
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ses_origin_ X1 X2
## 0.0000 0.0000 0.0000
## 1.0000 1.0000 0.0000
## 2.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: surprise
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3369 0.1135 2.9522 9.9873 2.0000 156.0000 0.0001
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.0556 0.2338 13.0682 0.0000 2.5937 3.5174
## X1 1.5069 0.3408 4.4212 0.0000 0.8337 2.1802
## X2 0.5234 0.3263 1.6041 0.1107 -0.1211 1.1679
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.5974 0.3568 2.2091 43.2773 2.0000 156.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.6852 0.2023 18.2201 0.0000 3.2857 4.0847
## X1 -1.5602 0.2948 -5.2916 0.0000 -2.1426 -0.9778
## X2 -2.6150 0.2822 -9.2649 0.0000 -3.1725 -2.0575
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2626 0.0689 1.6061 5.7762 2.0000 156.0000 0.0038
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.2778 0.1725 19.0059 0.0000 2.9371 3.6184
## X1 0.2222 0.2514 0.8839 0.3781 -0.2744 0.7188
## X2 0.7924 0.2407 3.2925 0.0012 0.3170 1.2678
##
## ***********************************************************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4712 0.2220 1.0302 8.7314 5.0000 153.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.6742 0.3793 12.3242 0.0000 3.9249 5.4235
## X1 0.0318 0.2301 0.1382 0.8903 -0.4227 0.4863
## X2 -0.0649 0.2414 -0.2689 0.7883 -0.5419 0.4121
## surprise 0.1380 0.0477 2.8936 0.0044 0.0438 0.2322
## sympathy -0.1716 0.0563 -3.0456 0.0027 -0.2828 -0.0603
## SE 0.1749 0.0666 2.6267 0.0095 0.0434 0.3065
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: blame
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2408 0.0580 1.2234 4.8012 2.0000 156.0000 0.0095
##
## Model:
## coeff se t p LLCI ULCI
## constant 5.0370 0.1505 33.4643 0.0000 4.7397 5.3344
## X1 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## ***********************************************************************
## 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 0.5463 0.2194 2.4897 0.0138 0.1129 0.9797
## X2 0.5945 0.2100 2.8305 0.0053 0.1796 1.0094
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.0580 4.8012 2.0000 156.0000 0.0095
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.0318 0.2301 0.1382 0.8903 -0.4227 0.4863
## X2 -0.0649 0.2414 -0.2689 0.7883 -0.5419 0.4121
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0010 0.1031 2.0000 153.0000 0.9021
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ses_origin_ -> surprise -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2080 0.1158 0.0306 0.4747
## X2 0.0722 0.0619 -0.0239 0.2169
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2080 0.0874 2.3789 0.0174
## X2 0.0722 0.0538 1.3429 0.1793
##
## ses_origin_ -> sympathy -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.2677 0.0982 0.1014 0.4848
## X2 0.4486 0.1479 0.1826 0.7687
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.2677 0.1028 2.6049 0.0092
## X2 0.4486 0.1559 2.8782 0.0040
##
## ses_origin_ -> SE -> blame
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0389 0.0566 -0.0571 0.1713
## X2 0.1386 0.0794 0.0081 0.3177
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0389 0.0493 0.7880 0.4307
## X2 0.1386 0.0694 1.9978 0.0457
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000