##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## PROCESS is now ready for use.
## Copyright 2022 by Andrew F. Hayes ALL RIGHTS RESERVED
## Workshop schedule at http://haskayne.ucalgary.ca/CCRAM
## ##
## Call:
## lm(formula = punishment ~ econ_sec_check, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.9587 -2.5851 -0.0247 2.1621 5.1621
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.83790 0.31449 15.383 <2e-16 ***
## econ_sec_check 0.18681 0.07921 2.358 0.0191 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.081 on 273 degrees of freedom
## Multiple R-squared: 0.01997, Adjusted R-squared: 0.01638
## F-statistic: 5.562 on 1 and 273 DF, p-value: 0.01906Mediation analysis: econ_sec_check -> SES -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : SES
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: SES
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7558 0.5712 1.2802 363.7133 1.0000 273.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 1.4862 0.1155 12.8663 0.0000 1.2588
## econ_sec_check 0.5548 0.0291 19.0713 0.0000 0.4976
## ULCI
## constant 1.7136
## econ_sec_check 0.6121
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1450 0.0210 9.5148 2.9222 2.0000 272.0000 0.0555
##
## Model:
## coeff se t p LLCI
## constant 4.9715 0.3991 12.4564 0.0000 4.1857
## econ_sec_check 0.2367 0.1211 1.9540 0.0517 -0.0018
## SES -0.0899 0.1650 -0.5447 0.5864 -0.4147
## ULCI
## constant 5.7572
## econ_sec_check 0.4751
## SES 0.2350
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.2367 0.1211 1.9540 0.0517 -0.0018 0.4751
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## SES -0.0499 0.0899 -0.2232 0.1297
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## SES -0.0499 0.0917 -0.5437 0.5866
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: econ_sec_check -> SEImpairment -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : SEImpairment
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: SEImpairment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1935 0.0374 2.9174 10.6167 1.0000 273.0000 0.0013
##
## Model:
## coeff se t p LLCI
## constant 3.5066 0.1744 20.1105 0.0000 3.1633
## econ_sec_check -0.1431 0.0439 -3.2583 0.0013 -0.2296
## ULCI
## constant 3.8499
## econ_sec_check -0.0566
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1521 0.0231 9.4943 3.2228 2.0000 272.0000 0.0414
##
## Model:
## coeff se t p LLCI
## constant 5.1983 0.4955 10.4908 0.0000 4.2227
## econ_sec_check 0.1721 0.0808 2.1312 0.0340 0.0131
## SEImpairment -0.1028 0.1092 -0.9412 0.3474 -0.3177
## ULCI
## constant 6.1738
## econ_sec_check 0.3311
## SEImpairment 0.1122
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.1721 0.0808 2.1312 0.0340 0.0131 0.3311
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## SEImpairment 0.0147 0.0174 -0.0176 0.0521
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## SEImpairment 0.0147 0.0170 0.8673 0.3858
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: econ_sec_check -> surprise -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : surprise
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: surprise
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2024 0.0410 4.3950 11.6570 1.0000 273.0000 0.0007
##
## Model:
## coeff se t p LLCI
## constant 2.8322 0.2140 13.2337 0.0000 2.4109
## econ_sec_check 0.1840 0.0539 3.4142 0.0007 0.0779
## ULCI
## constant 3.2536
## econ_sec_check 0.2902
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1484 0.0220 9.5053 3.0616 2.0000 272.0000 0.0484
##
## Model:
## coeff se t p LLCI
## constant 5.0282 0.4032 12.4693 0.0000 4.2343
## econ_sec_check 0.1992 0.0809 2.4605 0.0145 0.0398
## surprise -0.0672 0.0890 -0.7549 0.4509 -0.2424
## ULCI
## constant 5.8221
## econ_sec_check 0.3585
## surprise 0.1080
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.1992 0.0809 2.4605 0.0145 0.0398 0.3585
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## surprise -0.0124 0.0186 -0.0524 0.0236
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## surprise -0.0124 0.0174 -0.7087 0.4785
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: econ_sec_check -> sympathy -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : sympathy
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2530 0.0640 2.7708 18.6759 1.0000 273.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 2.9635 0.1699 17.4394 0.0000 2.6289
## econ_sec_check -0.1850 0.0428 -4.3216 0.0000 -0.2692
## ULCI
## constant 3.2980
## econ_sec_check -0.1007
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3490 0.1218 8.5355 18.8611 2.0000 272.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 6.6058 0.4336 15.2330 0.0000 5.7520
## econ_sec_check 0.0765 0.0776 0.9848 0.3256 -0.0764
## sympathy -0.5966 0.1062 -5.6159 0.0000 -0.8057
## ULCI
## constant 7.4595
## econ_sec_check 0.2293
## sympathy -0.3874
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.0765 0.0776 0.9848 0.3256 -0.0764 0.2293
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## sympathy 0.1103 0.0333 0.0504 0.1819
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## sympathy 0.1103 0.0325 3.3913 0.0007
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000SE1, SE2
Mediation analysis: econ_sec_check -> SE -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : SE
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1973 0.0389 1.6950 11.0598 1.0000 273.0000 0.0010
##
## Model:
## coeff se t p LLCI
## constant 3.6543 0.1329 27.4951 0.0000 3.3926
## econ_sec_check 0.1113 0.0335 3.3256 0.0010 0.0454
## ULCI
## constant 3.9159
## econ_sec_check 0.1772
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3373 0.1138 8.6135 17.4583 2.0000 272.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 2.1628 0.5817 3.7182 0.0002 1.0176
## econ_sec_check 0.1053 0.0770 1.3681 0.1724 -0.0462
## SE 0.7320 0.1364 5.3655 0.0000 0.4634
## ULCI
## constant 3.3080
## econ_sec_check 0.2569
## SE 1.0007
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.1053 0.0770 1.3681 0.1724 -0.0462 0.2569
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## SE 0.0815 0.0301 0.0283 0.1459
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## SE 0.0815 0.0292 2.7919 0.0052
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000SFC1, SFC2, SFC3, and SFC4
Mediation analysis: econ_sec_check -> SFC -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : SFC
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: SFC
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2576 0.0663 1.3390 19.4004 1.0000 273.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 3.4065 0.1181 28.8375 0.0000 3.1740
## econ_sec_check 0.1310 0.0298 4.4046 0.0000 0.0725
## ULCI
## constant 3.6391
## econ_sec_check 0.1896
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2656 0.0705 9.0337 10.3205 2.0000 272.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 2.7779 0.6172 4.5008 0.0000 1.5628
## econ_sec_check 0.1076 0.0800 1.3448 0.1798 -0.0499
## SFC 0.6047 0.1572 3.8468 0.0001 0.2952
## ULCI
## constant 3.9929
## econ_sec_check 0.2650
## SFC 0.9142
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.1076 0.0800 1.3448 0.1798 -0.0499 0.2650
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## SFC 0.0792 0.0282 0.0310 0.1396
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## SFC 0.0792 0.0277 2.8559 0.0043
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000SE3
Mediation analysis: econ_sec_check -> upbringing -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M : upbringing
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: upbringing
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3325 0.1106 3.2166 33.9343 1.0000 273.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 3.9915 0.1831 21.8007 0.0000 3.6311
## econ_sec_check -0.2686 0.0461 -5.8253 0.0000 -0.3594
## ULCI
## constant 4.3520
## econ_sec_check -0.1778
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1643 0.0270 9.4568 3.7743 2.0000 272.0000 0.0242
##
## Model:
## coeff se t p LLCI
## constant 5.4188 0.5197 10.4260 0.0000 4.3956
## econ_sec_check 0.1477 0.0838 1.7618 0.0792 -0.0173
## upbringing -0.1455 0.1038 -1.4025 0.1619 -0.3498
## ULCI
## constant 6.4421
## econ_sec_check 0.3128
## upbringing 0.0588
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.1477 0.0838 1.7618 0.0792 -0.0173 0.3128
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## upbringing 0.0391 0.0293 -0.0192 0.0979
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## upbringing 0.0391 0.0291 1.3449 0.1787
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000Mediation analysis: econ_sec_check -> parallel -> punishment
##
## ********************* PROCESS for R Version 4.1.1 *********************
##
## Written by Andrew F. Hayes, Ph.D. www.afhayes.com
## Documentation available in Hayes (2022). www.guilford.com/p/hayes3
##
## ***********************************************************************
##
## Model : 4
## Y : punishment
## X : econ_sec_check
## M1 : sympathy
## M2 : SE
## M3 : SFC
##
## Sample size: 275
##
## Custom seed: 1234
##
##
## ***********************************************************************
## Outcome Variable: sympathy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2530 0.0640 2.7708 18.6759 1.0000 273.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 2.9635 0.1699 17.4394 0.0000 2.6289
## econ_sec_check -0.1850 0.0428 -4.3216 0.0000 -0.2692
## ULCI
## constant 3.2980
## econ_sec_check -0.1007
##
## ***********************************************************************
## Outcome Variable: SE
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1973 0.0389 1.6950 11.0598 1.0000 273.0000 0.0010
##
## Model:
## coeff se t p LLCI
## constant 3.6543 0.1329 27.4951 0.0000 3.3926
## econ_sec_check 0.1113 0.0335 3.3256 0.0010 0.0454
## ULCI
## constant 3.9159
## econ_sec_check 0.1772
##
## ***********************************************************************
## Outcome Variable: SFC
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2576 0.0663 1.3390 19.4004 1.0000 273.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 3.4065 0.1181 28.8375 0.0000 3.1740
## econ_sec_check 0.1310 0.0298 4.4046 0.0000 0.0725
## ULCI
## constant 3.6391
## econ_sec_check 0.1896
##
## ***********************************************************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.3941 0.1553 8.2702 12.4146 4.0000 270.0000 0.0000
##
## Model:
## coeff se t p LLCI
## constant 4.2024 1.0337 4.0654 0.0001 2.1673
## econ_sec_check 0.0520 0.0773 0.6726 0.5018 -0.1002
## sympathy -0.4162 0.1287 -3.2333 0.0014 -0.6696
## SE 0.4807 0.1563 3.0755 0.0023 0.1730
## SFC 0.0329 0.1867 0.1765 0.8600 -0.3346
## ULCI
## constant 6.2375
## econ_sec_check 0.2042
## sympathy -0.1628
## SE 0.7884
## SFC 0.4005
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: punishment
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.1413 0.0200 9.4903 5.5620 1.0000 273.0000 0.0191
##
## Model:
## coeff se t p LLCI
## constant 4.8379 0.3145 15.3833 0.0000 4.2188
## econ_sec_check 0.1868 0.0792 2.3584 0.0191 0.0309
## ULCI
## constant 5.4570
## econ_sec_check 0.3427
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ************ TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************
##
## Total effect of X on Y:
## effect se t p LLCI ULCI
## 0.1868 0.0792 2.3584 0.0191 0.0309 0.3427
##
## Direct effect of X on Y:
## effect se t p LLCI ULCI
## 0.0520 0.0773 0.6726 0.5018 -0.1002 0.2042
##
## Indirect effect(s) of X on Y:
## Effect BootSE BootLLCI BootULCI
## TOTAL 0.1348 0.0400 0.0603 0.2152
## sympathy 0.0770 0.0305 0.0236 0.1436
## SE 0.0535 0.0248 0.0131 0.1088
## SFC 0.0043 0.0246 -0.0466 0.0519
##
## Normal theory test for indirect effect(s):
## Effect se Z p
## sympathy 0.0770 0.0302 2.5456 0.0109
## SE 0.0535 0.0243 2.2049 0.0275
## SFC 0.0043 0.0251 0.1720 0.8634
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000