##
## ********************* 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
## α = 0.931 95% CI [ 0.916 , 0.945 ]
✓ Composite trust created (α meets threshold of 0.8
)
α = 0.963 95% CI [ 0.956 , 0.97 ]
✓ Composite ability created (α meets threshold of 0.8
)
α = 0.889 95% CI [ 0.868 , 0.909 ]
✓ Composite benevolence created (α meets threshold of
0.8 )
α = 0.88 95% CI [ 0.857 , 0.902 ]
✓ Composite integrity created (α meets threshold of 0.8
)
α = 0.872 95% CI [ 0.85 , 0.895 ]
✓ Composite autonomy created (α meets threshold of 0.8
)
α = 0.978 95% CI [ 0.973 , 0.982 ]
✓ Composite ai_attitudes created (α meets threshold of
0.8 )
##
## Call:
## lm(formula = trust ~ ai_training_1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.0998 -0.4255 0.2373 0.5745 1.9002
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.43699 0.15747 21.826 <2e-16 ***
## ai_training_1 0.66283 0.07304 9.074 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.105 on 333 degrees of freedom
## Multiple R-squared: 0.1983, Adjusted R-squared: 0.1958
## F-statistic: 82.34 on 1 and 333 DF, p-value: < 2.2e-16##
## ********************* 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 : trust
## X : ai_training_1
## M : ability
##
## Sample size: 335
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: ability
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4671 0.2181 1.0505 46.3165 2.0000 332.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.2141 0.0952 44.2834 0.0000 4.0269 4.4013
## X1 0.8111 0.1377 5.8895 0.0000 0.5402 1.0820
## X2 1.2889 0.1355 9.5141 0.0000 1.0224 1.5554
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.9052 0.8194 0.2769 500.4713 3.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.0523 0.1284 0.4074 0.6840 -0.2003 0.3049
## X1 0.0756 0.0743 1.0172 0.3098 -0.0706 0.2218
## X2 0.1036 0.0785 1.3200 0.1877 -0.0508 0.2579
## ability 0.9470 0.0282 33.6081 0.0000 0.8916 1.0024
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4505 0.2030 1.2182 42.2712 2.0000 332.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0431 0.1025 39.4538 0.0000 3.8415 4.2447
## X1 0.8437 0.1483 5.6890 0.0000 0.5520 1.1354
## X2 1.3242 0.1459 9.0768 0.0000 1.0372 1.6111
##
## ***********************************************************************
## 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 0.8437 0.1483 5.6890 0.0000 0.5520 1.1354
## X2 1.3242 0.1459 9.0768 0.0000 1.0372 1.6111
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2030 42.2712 2.0000 332.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.0756 0.0743 1.0172 0.3098 -0.0706 0.2218
## X2 0.1036 0.0785 1.3200 0.1877 -0.0508 0.2579
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0010 0.9312 2.0000 331.0000 0.3951
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ai_training_1 -> ability -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.7681 0.1423 0.4935 1.0484
## X2 1.2206 0.1428 0.9400 1.5055
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.7681 0.1325 5.7986 0.0000
## X2 1.2206 0.1334 9.1506 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000##
## ********************* 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 : trust
## X : ai_training_1
## M : benevolence
##
## Sample size: 334
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: benevolence
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2744 0.0753 0.9763 13.4796 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.4713 0.0917 48.7375 0.0000 4.2908 4.6517
## X1 0.0791 0.1328 0.5954 0.5520 -0.1821 0.3402
## X2 0.6284 0.1309 4.8011 0.0000 0.3709 0.8859
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6546 0.4285 0.8777 82.4857 3.0000 330.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.4003 0.2487 5.6297 0.0000 0.9110 1.8896
## X1 0.7970 0.1260 6.3275 0.0000 0.5492 1.0447
## X2 0.9649 0.1284 7.5173 0.0000 0.7124 1.2174
## benevolence 0.5911 0.0521 11.3414 0.0000 0.4885 0.6936
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4536 0.2058 1.2162 42.8806 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0431 0.1024 39.4865 0.0000 3.8417 4.2445
## X1 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## ***********************************************************************
## 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 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2058 42.8806 2.0000 331.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.7970 0.1260 6.3275 0.0000 0.5492 1.0447
## X2 0.9649 0.1284 7.5173 0.0000 0.7124 1.2174
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.1148 33.1336 2.0000 330.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ai_training_1 -> benevolence -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0467 0.0845 -0.1163 0.2180
## X2 0.3714 0.0878 0.2085 0.5548
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0467 0.0789 0.5923 0.5537
## X2 0.3714 0.0843 4.4067 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000
##
## NOTE: Some cases with missing data were deleted. The number of deleted cases was: 1##
## ********************* 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 : trust
## X : ai_training_1
## M : integrity
##
## Sample size: 334
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: integrity
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4445 0.1975 0.9362 40.7413 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8362 0.0898 42.7007 0.0000 3.6595 4.0129
## X1 0.4688 0.1300 3.6060 0.0004 0.2131 0.7246
## X2 1.1519 0.1282 8.9864 0.0000 0.8997 1.4040
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7250 0.5257 0.7285 121.9017 3.0000 330.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.2683 0.2022 6.2733 0.0000 0.8706 1.6661
## X1 0.5046 0.1169 4.3156 0.0000 0.2746 0.7346
## X2 0.5032 0.1261 3.9900 0.0001 0.2551 0.7513
## integrity 0.7233 0.0485 14.9179 0.0000 0.6279 0.8187
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4536 0.2058 1.2162 42.8806 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0431 0.1024 39.4865 0.0000 3.8417 4.2445
## X1 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## ***********************************************************************
## 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 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2058 42.8806 2.0000 331.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.5046 0.1169 4.3156 0.0000 0.2746 0.7346
## X2 0.5032 0.1261 3.9900 0.0001 0.2551 0.7513
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0329 11.4601 2.0000 330.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ai_training_1 -> integrity -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.3391 0.1051 0.1388 0.5525
## X2 0.8332 0.1182 0.6102 1.0771
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.3391 0.0970 3.4976 0.0005
## X2 0.8332 0.1084 7.6850 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000
##
## NOTE: Some cases with missing data were deleted. The number of deleted cases was: 1##
## ********************* 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 : trust
## X : ai_training_1
## M : autonomy
##
## Sample size: 334
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: autonomy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6014 0.3616 1.0558 93.7578 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.4310 0.0954 35.9638 0.0000 3.2434 3.6187
## X1 0.8834 0.1381 6.3987 0.0000 0.6118 1.1550
## X2 1.8636 0.1361 13.6911 0.0000 1.5958 2.1314
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7542 0.5689 0.6622 145.1382 3.0000 330.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 1.5533 0.1674 9.2803 0.0000 1.2240 1.8826
## X1 0.2026 0.1159 1.7480 0.0814 -0.0254 0.4306
## X2 -0.0160 0.1349 -0.1186 0.9057 -0.2814 0.2494
## autonomy 0.7257 0.0435 16.6706 0.0000 0.6400 0.8113
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4536 0.2058 1.2162 42.8806 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0431 0.1024 39.4865 0.0000 3.8417 4.2445
## X1 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## ***********************************************************************
## 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 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2058 42.8806 2.0000 331.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.2026 0.1159 1.7480 0.0814 -0.0254 0.4306
## X2 -0.0160 0.1349 -0.1186 0.9057 -0.2814 0.2494
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0063 2.4247 2.0000 330.0000 0.0901
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ai_training_1 -> autonomy -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.6411 0.1267 0.3981 0.8958
## X2 1.3524 0.1489 1.0646 1.6485
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.6411 0.1075 5.9644 0.0000
## X2 1.3524 0.1280 10.5689 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000
##
## NOTE: Some cases with missing data were deleted. The number of deleted cases was: 1##
## ********************* 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 : trust
## X : ai_training_1
## M : ai_use
##
## Sample size: 329
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: ai_use
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.7307 0.5339 1.5252 186.7195 2.0000 326.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.8142 0.1162 41.4382 0.0000 4.5856 5.0427
## X1 -1.6795 0.1678 -10.0083 0.0000 -2.0097 -1.3494
## X2 -3.1802 0.1647 -19.3133 0.0000 -3.5042 -2.8563
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4659 0.2171 1.2190 30.0402 3.0000 325.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.5175 0.2600 17.3739 0.0000 4.0059 5.0290
## X1 0.6887 0.1715 4.0151 0.0001 0.3513 1.0262
## X2 1.0271 0.2156 4.7649 0.0000 0.6031 1.4512
## ai_use -0.1011 0.0495 -2.0409 0.0421 -0.1985 -0.0036
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4550 0.2071 1.2308 42.5644 2.0000 326.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0310 0.1044 38.6237 0.0000 3.8257 4.2363
## X1 0.8584 0.1508 5.6944 0.0000 0.5619 1.1550
## X2 1.3485 0.1479 9.1161 0.0000 1.0575 1.6395
##
## ***********************************************************************
## 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 0.8584 0.1508 5.6944 0.0000 0.5619 1.1550
## X2 1.3485 0.1479 9.1161 0.0000 1.0575 1.6395
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2071 42.5644 2.0000 326.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 0.6887 0.1715 4.0151 0.0001 0.3513 1.0262
## X2 1.0271 0.2156 4.7649 0.0000 0.6031 1.4512
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0583 12.1061 2.0000 325.0000 0.0000
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ai_training_1 -> ai_use -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1697 0.0831 0.0030 0.3322
## X2 0.3214 0.1544 0.0059 0.6187
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1697 0.0853 1.9902 0.0466
## X2 0.3214 0.1586 2.0269 0.0427
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000
##
## NOTE: Some cases with missing data were deleted. The number of deleted cases was: 6##
## ********************* 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 : trust
## X : ai_training_1
## M1 : ability
## M2 : benevolence
## M3 : integrity
## M4 : autonomy
##
## Sample size: 334
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: ability
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4723 0.2231 1.0434 47.5245 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.2141 0.0948 44.4339 0.0000 4.0275 4.4006
## X1 0.8111 0.1372 5.9095 0.0000 0.5411 1.0811
## X2 1.3053 0.1353 9.6461 0.0000 1.0391 1.5715
##
## ***********************************************************************
## Outcome Variable: benevolence
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.2744 0.0753 0.9763 13.4796 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.4713 0.0917 48.7375 0.0000 4.2908 4.6517
## X1 0.0791 0.1328 0.5954 0.5520 -0.1821 0.3402
## X2 0.6284 0.1309 4.8011 0.0000 0.3709 0.8859
##
## ***********************************************************************
## Outcome Variable: integrity
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4445 0.1975 0.9362 40.7413 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.8362 0.0898 42.7007 0.0000 3.6595 4.0129
## X1 0.4688 0.1300 3.6060 0.0004 0.2131 0.7246
## X2 1.1519 0.1282 8.9864 0.0000 0.8997 1.4040
##
## ***********************************************************************
## Outcome Variable: autonomy
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.6014 0.3616 1.0558 93.7578 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 3.4310 0.0954 35.9638 0.0000 3.2434 3.6187
## X1 0.8834 0.1381 6.3987 0.0000 0.6118 1.1550
## X2 1.8636 0.1361 13.6911 0.0000 1.5958 2.1314
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.9124 0.8325 0.2596 270.9567 6.0000 327.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 0.0131 0.1454 0.0899 0.9284 -0.2730 0.2992
## X1 -0.0110 0.0759 -0.1449 0.8849 -0.1603 0.1383
## X2 -0.1060 0.0873 -1.2138 0.2257 -0.2778 0.0658
## ability 0.8362 0.0391 21.3804 0.0000 0.7592 0.9131
## benevolence -0.0551 0.0485 -1.1369 0.2564 -0.1504 0.0402
## integrity 0.0250 0.0587 0.4251 0.6710 -0.0906 0.1405
## autonomy 0.1915 0.0438 4.3756 0.0000 0.1054 0.2775
##
## ************************ TOTAL EFFECT MODEL ***************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4536 0.2058 1.2162 42.8806 2.0000 331.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0431 0.1024 39.4865 0.0000 3.8417 4.2445
## X1 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## ***********************************************************************
## 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 0.8437 0.1482 5.6937 0.0000 0.5522 1.1352
## X2 1.3364 0.1461 9.1474 0.0000 1.0490 1.6237
##
## Omnibus test of total effect of X on Y:
## R2-chng F df1 df2 p
## 0.2058 42.8806 2.0000 331.0000 0.0000
## ----------
##
## Relative direct effects of X on Y:
## effect se t p LLCI ULCI
## X1 -0.0110 0.0759 -0.1449 0.8849 -0.1603 0.1383
## X2 -0.1060 0.0873 -1.2138 0.2257 -0.2778 0.0658
##
## Omnibus test of direct effect of X on Y:
## R2-chng F df1 df2 p
## 0.0010 0.9923 2.0000 327.0000 0.3718
##
## ----------
##
## Relative indirect effects of X on Y:
##
## ai_training_1 -> ability -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.6782 0.1294 0.4319 0.9382
## X2 1.0914 0.1345 0.8363 1.3660
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.6782 0.1192 5.6901 0.0000
## X2 1.0914 0.1242 8.7847 0.0000
##
## ai_training_1 -> benevolence -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 -0.0044 0.0114 -0.0324 0.0155
## X2 -0.0346 0.0348 -0.1096 0.0282
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 -0.0044 0.0105 -0.4161 0.6774
## X2 -0.0346 0.0319 -1.0842 0.2783
##
## ai_training_1 -> integrity -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.0117 0.0335 -0.0567 0.0785
## X2 0.0288 0.0798 -0.1307 0.1814
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.0117 0.0288 0.4070 0.6840
## X2 0.0288 0.0681 0.4220 0.6730
##
## ai_training_1 -> autonomy -> trust
##
## Effect BootSE BootLLCI BootULCI
## X1 0.1691 0.0590 0.0672 0.2972
## X2 0.3568 0.1068 0.1600 0.5782
##
## Normal theory test for relative indirect effects:
## Effect se Z p
## X1 0.1691 0.0472 3.5821 0.0003
## X2 0.3568 0.0858 4.1578 0.0000
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000
##
## NOTE: Some cases with missing data were deleted. The number of deleted cases was: 1##
## ********************* 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 : 1
## Y : trust
## X : ai_training_1
## W : comp_check_2
##
## Sample size: 335
##
## Custom seed: 1234
##
## Coding of categorical X variable for analysis:
## ai_training_1 X1 X2
## 1.0000 0.0000 0.0000
## 2.0000 1.0000 0.0000
## 3.0000 0.0000 1.0000
##
## ***********************************************************************
## Outcome Variable: trust
##
## Model Summary:
## R R-sq MSE F df1 df2 p
## 0.4604 0.2120 1.2154 17.6975 5.0000 329.0000 0.0000
##
## Model:
## coeff se t p LLCI ULCI
## constant 4.0250 0.1029 39.1109 0.0000 3.8225 4.2274
## X1 0.8682 0.1487 5.8396 0.0000 0.5758 1.1607
## X2 1.3418 0.1462 9.1779 0.0000 1.0542 1.6294
## comp_check_2 -0.0836 0.0491 -1.7025 0.0896 -0.1801 0.0130
## Int_1 0.0360 0.0713 0.5045 0.6142 -0.1043 0.1763
## Int_2 0.0887 0.0729 1.2163 0.2247 -0.0548 0.2322
##
## Product terms key:
## Int_1 : X1 x comp_check_2
## Int_2 : X2 x comp_check_2
##
## Test(s) of highest order unconditional interaction(s):
## R2-chng F df1 df2 p
## X*W 0.0036 0.7419 2.0000 329.0000 0.4770
##
## ***********************************************************************
## Bootstrapping in progress. Please wait.
##
## ********** BOOTSTRAP RESULTS FOR REGRESSION MODEL PARAMETERS **********
##
## Outcome variable: trust
##
## Coeff BootMean BootSE BootLLCI BootULCI
## constant 4.0250 4.0237 0.1405 3.7435 4.2928
## X1 0.8682 0.8698 0.1636 0.5491 1.1917
## X2 1.3418 1.3428 0.1571 1.0323 1.6565
## comp_check_2 -0.0836 -0.0834 0.0626 -0.2051 0.0384
## Int_1 0.0360 0.0360 0.0743 -0.1083 0.1822
## Int_2 0.0887 0.0889 0.0718 -0.0523 0.2288
##
## ******************** ANALYSIS NOTES AND ERRORS ************************
##
## Level of confidence for all confidence intervals in output: 95
##
## Number of bootstraps for percentile bootstrap confidence intervals: 10000
##
## NOTE: The following variables were mean centered prior to analysis:
## comp_check_2