Main Effects

Dependent Variable: Effective

Regression Estimates

R² = 0.021, Adjusted R² = 0.015, F(2, 295) = 3.186

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.340	0.114	46.769	0.000	***
conditionmedian	median	-0.269	0.162	-1.664	0.097	ns
conditionaverage	average	-0.401	0.162	-2.475	0.014

Planned Contrasts

Contrast	Estimate	SE	t ratio	df	p value
median vs max	-0.269	0.162	-1.664	295	0.097	ns
average vs max	-0.401	0.162	-2.475	295	0.014
average vs median	-0.131	0.162	-0.809	295	0.419	ns

Dependent Variable: Compare

Regression Estimates

R² = 0.012, Adjusted R² = 0.005, F(2, 295) = 1.812

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.180	0.118	43.995	0.000	***
conditionmedian	median	-0.210	0.167	-1.260	0.209	ns
conditionaverage	average	-0.311	0.167	-1.865	0.063	ns

Planned Contrasts

Contrast	Estimate	SE	t ratio	df	p value
median vs max	-0.210	0.167	-1.260	295	0.209	ns
average vs max	-0.311	0.167	-1.865	295	0.063	ns
average vs median	-0.101	0.167	-0.604	295	0.547	ns

Dependent Variable: Purchase

Regression Estimates

R² = 0.01, Adjusted R² = 0.003, F(2, 295) = 1.419

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.150	0.178	23.254	0.000	***
conditionmedian	median	-0.322	0.253	-1.272	0.205	ns
conditionaverage	average	-0.403	0.253	-1.591	0.113	ns

Planned Contrasts

Contrast	Estimate	SE	t ratio	df	p value
median vs max	-0.322	0.253	-1.272	295	0.205	ns
average vs max	-0.403	0.253	-1.591	295	0.113	ns
average vs median	-0.081	0.254	-0.319	295	0.750	ns

Dependent Variable: Maximum

Regression Estimates

R² = 0.028, Adjusted R² = 0.021, F(2, 295) = 4.191

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.370	0.130	41.265	0.000	***
conditionmedian	median	-0.481	0.185	-2.608	0.010	**
conditionaverage	average	-0.441	0.185	-2.389	0.018

Planned Contrasts

Contrast	Estimate	SE	t ratio	df	p value
median vs max	-0.481	0.185	-2.608	295	0.010	**
average vs max	-0.441	0.185	-2.389	295	0.018
average vs median	0.040	0.185	0.218	295	0.827	ns

Dependent Variable: Trust

Regression Estimates

R² = 0.007, Adjusted R² = 0, F(2, 295) = 1.03

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.740	0.146	32.423	0.000	***
conditionmedian	median	-0.285	0.207	-1.377	0.169	ns
conditionaverage	average	-0.215	0.207	-1.036	0.301	ns

Planned Contrasts

Contrast	Estimate	SE	t ratio	df	p value
median vs max	-0.285	0.207	-1.377	295	0.169	ns
average vs max	-0.215	0.207	-1.036	295	0.301	ns
average vs median	0.071	0.208	0.340	295	0.734	ns

Dependent Variable: Easy

Regression Estimates

R² = 0.011, Adjusted R² = 0.004, F(2, 295) = 1.643

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.230	0.149	35.087	0.000	***
conditionmedian	median	-0.382	0.211	-1.805	0.072	ns
conditionaverage	average	-0.220	0.211	-1.041	0.299	ns

Planned Contrasts

Contrast	Estimate	SE	t ratio	df	p value
median vs max	-0.382	0.211	-1.805	295	0.072	ns
average vs max	-0.220	0.211	-1.041	295	0.299	ns
average vs median	0.162	0.212	0.763	295	0.446	ns

Models with Demographic Covariates

Dependent Variable: Effective

Covariate: Age

R² = 0.021, Adjusted R² = 0.011, F(3, 294) = 2.118

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.349	0.181	29.543	0.000	***
conditionmedian	median	-0.270	0.162	-1.662	0.098	ns
conditionaverage	average	-0.400	0.162	-2.466	0.014
age	age	0.000	0.006	-0.061	0.951	ns

Covariate: Gender

R² = 0.022, Adjusted R² = 0.012, F(3, 294) = 2.25

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.455	0.216	25.232	0.000	***
conditionmedian	median	-0.270	0.162	-1.669	0.096	ns
conditionaverage	average	-0.400	0.162	-2.470	0.014
gender	gender	-0.076	0.122	-0.625	0.533	ns

Covariate: Income

R² = 0.022, Adjusted R² = 0.012, F(3, 294) = 2.229

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.412	0.170	31.746	0.000	***
conditionmedian	median	-0.263	0.162	-1.620	0.106	ns
conditionaverage	average	-0.399	0.162	-2.459	0.014
income	income	-0.020	0.035	-0.573	0.567	ns

Dependent Variable: Compare

Covariate: Age

R² = 0.016, Adjusted R² = 0.006, F(3, 294) = 1.598

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.024	0.186	26.963	0.000	***
conditionmedian	median	-0.203	0.167	-1.217	0.225	ns
conditionaverage	average	-0.318	0.167	-1.907	0.058	ns
age	age	0.007	0.006	1.081	0.281	ns

Covariate: Gender

R² = 0.014, Adjusted R² = 0.004, F(3, 294) = 1.38

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.317	0.223	23.854	0.000	***
conditionmedian	median	-0.212	0.167	-1.267	0.206	ns
conditionaverage	average	-0.311	0.167	-1.861	0.064	ns
gender	gender	-0.090	0.125	-0.722	0.471	ns

Covariate: Income

R² = 0.013, Adjusted R² = 0.003, F(3, 294) = 1.337

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.262	0.176	29.932	0.000	***
conditionmedian	median	-0.203	0.167	-1.214	0.226	ns
conditionaverage	average	-0.309	0.167	-1.849	0.065	ns
income	income	-0.023	0.036	-0.628	0.531	ns

Dependent Variable: Purchase

Covariate: Age

R² = 0.014, Adjusted R² = 0.004, F(3, 294) = 1.369

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.396	0.282	15.570	0.000	***
conditionmedian	median	-0.333	0.253	-1.315	0.189	ns
conditionaverage	average	-0.391	0.253	-1.546	0.123	ns
age	age	-0.010	0.009	-1.125	0.261	ns

Covariate: Gender

R² = 0.012, Adjusted R² = 0.002, F(3, 294) = 1.189

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.395	0.338	13.015	0.000	***
conditionmedian	median	-0.324	0.253	-1.281	0.201	ns
conditionaverage	average	-0.402	0.253	-1.587	0.114	ns
gender	gender	-0.162	0.190	-0.855	0.393	ns

Covariate: Income

R² = 0.01, Adjusted R² = 0, F(3, 294) = 0.966

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.203	0.267	15.764	0.000	***
conditionmedian	median	-0.317	0.254	-1.249	0.213	ns
conditionaverage	average	-0.401	0.253	-1.582	0.115	ns
income	income	-0.015	0.055	-0.265	0.791	ns

Dependent Variable: Maximum

Covariate: Age

R² = 0.028, Adjusted R² = 0.018, F(3, 294) = 2.785

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.368	0.206	26.013	0.000	***
conditionmedian	median	-0.481	0.185	-2.601	0.010	**
conditionaverage	average	-0.441	0.185	-2.383	0.018
age	age	0.000	0.007	0.014	0.989	ns

Covariate: Gender

R² = 0.028, Adjusted R² = 0.018, F(3, 294) = 2.785

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.367	0.247	21.767	0.000	***
conditionmedian	median	-0.481	0.185	-2.603	0.010	**
conditionaverage	average	-0.441	0.185	-2.385	0.018
gender	gender	0.002	0.139	0.015	0.988	ns

Covariate: Income

R² = 0.028, Adjusted R² = 0.019, F(3, 294) = 2.87

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.442	0.194	28.002	0.000	***
conditionmedian	median	-0.475	0.185	-2.565	0.011
conditionaverage	average	-0.439	0.185	-2.375	0.018
income	income	-0.020	0.040	-0.500	0.618	ns

Dependent Variable: Trust

Covariate: Age

R² = 0.007, Adjusted R² = -0.003, F(3, 294) = 0.686

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.730	0.232	20.406	0.000	***
conditionmedian	median	-0.285	0.208	-1.372	0.171	ns
conditionaverage	average	-0.215	0.208	-1.036	0.301	ns
age	age	0.000	0.008	0.055	0.956	ns

Covariate: Gender

R² = 0.007, Adjusted R² = -0.003, F(3, 294) = 0.693

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.702	0.277	16.979	0.000	***
conditionmedian	median	-0.285	0.208	-1.373	0.171	ns
conditionaverage	average	-0.215	0.208	-1.035	0.302	ns
gender	gender	0.025	0.156	0.160	0.873	ns

Covariate: Income

R² = 0.014, Adjusted R² = 0.004, F(3, 294) = 1.415

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.978	0.218	22.877	0.000	***
conditionmedian	median	-0.265	0.207	-1.278	0.202	ns
conditionaverage	average	-0.208	0.207	-1.007	0.315	ns
income	income	-0.066	0.045	-1.475	0.141	ns

Dependent Variable: Easy

Covariate: Age

R² = 0.022, Adjusted R² = 0.012, F(3, 294) = 2.156

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	4.906	0.235	20.869	0.000	***
conditionmedian	median	-0.367	0.211	-1.741	0.083	ns
conditionaverage	average	-0.235	0.211	-1.114	0.266	ns
age	age	0.014	0.008	1.777	0.077	ns

Covariate: Gender

R² = 0.012, Adjusted R² = 0.002, F(3, 294) = 1.157

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.125	0.282	18.152	0.000	***
conditionmedian	median	-0.380	0.212	-1.798	0.073	ns
conditionaverage	average	-0.220	0.212	-1.041	0.299	ns
gender	gender	0.070	0.159	0.440	0.660	ns

Covariate: Income

R² = 0.018, Adjusted R² = 0.008, F(3, 294) = 1.796

	Term	Estimate	Std. Error	t value	p value
(Intercept)	Intercept (max)	5.468	0.222	24.641	0.000	***
conditionmedian	median	-0.361	0.211	-1.708	0.089	ns
conditionaverage	average	-0.213	0.211	-1.012	0.312	ns
income	income	-0.066	0.046	-1.446	0.149	ns

==============================
Mediation: condition_median -> effective -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                         
  Model: 4               
      Y: purchase        
      X: condition_median
      M: effective       

Sample size: 298

Random seed: 145111


*********************************************************************** 
Outcome Variable: effective

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0287    0.0008    1.3262    0.2442    1.0000  296.0000    0.6215

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            5.1407    0.0816   62.9708    0.0000    4.9800    5.3014
condition_median   -0.0700    0.1416   -0.4942    0.6215   -0.3487    0.2087

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.6262    0.3921    1.9546   95.1411    2.0000  295.0000    0.0000

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant           -1.0475    0.3760   -2.7856    0.0057   -1.7875   -0.3074
condition_median   -0.0534    0.1720   -0.3106    0.7564   -0.3920    0.2851
effective           0.9721    0.0706   13.7762    0.0000    0.8332    1.1110

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
    -0.0534    0.1720   -0.3106    0.7564   -0.3920    0.2851

Indirect effect(s) of X on Y:
             Effect    BootSE  BootLLCI  BootULCI
effective   -0.0680    0.1395   -0.3486    0.2009

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_median -> compare -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                         
  Model: 4               
      Y: purchase        
      X: condition_median
      M: compare         

Sample size: 298

Random seed: 907080


*********************************************************************** 
Outcome Variable: compare

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0222    0.0005    1.3979    0.1453    1.0000  296.0000    0.7033

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            5.0251    0.0838   59.9560    0.0000    4.8602    5.1901
condition_median   -0.0554    0.1454   -0.3812    0.7033   -0.3416    0.2307

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.6373    0.4061    1.9096  100.8599    2.0000  295.0000    0.0000

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant           -0.8926    0.3552   -2.5134    0.0125   -1.5916   -0.1937
condition_median   -0.0681    0.1700   -0.4003    0.6892   -0.4026    0.2665
compare             0.9636    0.0679   14.1848    0.0000    0.8299    1.0973

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
    -0.0681    0.1700   -0.4003    0.6892   -0.4026    0.2665

Indirect effect(s) of X on Y:
           Effect    BootSE  BootLLCI  BootULCI
compare   -0.0534    0.1454   -0.3464    0.2201

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_median -> maximum -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                         
  Model: 4               
      Y: purchase        
      X: condition_median
      M: maximum         

Sample size: 298

Random seed: 673303


*********************************************************************** 
Outcome Variable: maximum

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0939    0.0088    1.7205    2.6350    1.0000  296.0000    0.1056

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            5.1508    0.0930   55.3956    0.0000    4.9678    5.3337
condition_median   -0.2619    0.1613   -1.6233    0.1056   -0.5793    0.0556

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.5299    0.2808    2.3126   57.5879    2.0000  295.0000    0.0000

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            0.2315    0.3635    0.6371    0.5246   -0.4837    0.9468
condition_median    0.0676    0.1879    0.3597    0.7194   -0.3021    0.4373
maximum             0.7219    0.0674   10.7123    0.0000    0.5893    0.8545

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
     0.0676    0.1879    0.3597    0.7194   -0.3021    0.4373

Indirect effect(s) of X on Y:
           Effect    BootSE  BootLLCI  BootULCI
maximum   -0.1890    0.1290   -0.4581    0.0534

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_median -> trust -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                         
  Model: 4               
      Y: purchase        
      X: condition_median
      M: trust           

Sample size: 298

Random seed: 894697


*********************************************************************** 
Outcome Variable: trust

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0576    0.0033    2.1377    0.9867    1.0000  296.0000    0.3214

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            4.6332    0.1036   44.7022    0.0000    4.4292    4.8371
condition_median   -0.1786    0.1798   -0.9933    0.3214   -0.5325    0.1753

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.6553    0.4294    1.8348  110.9957    2.0000  295.0000    0.0000

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            0.2370    0.2673    0.8866    0.3760   -0.2891    0.7631
condition_median    0.0217    0.1669    0.1299    0.8968   -0.3067    0.3501
trust               0.8013    0.0538   14.8815    0.0000    0.6954    0.9073

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
     0.0217    0.1669    0.1299    0.8968   -0.3067    0.3501

Indirect effect(s) of X on Y:
         Effect    BootSE  BootLLCI  BootULCI
trust   -0.1431    0.1465   -0.4338    0.1386

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_median -> easy -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                         
  Model: 4               
      Y: purchase        
      X: condition_median
      M: easy            

Sample size: 298

Random seed: 239549


*********************************************************************** 
Outcome Variable: easy

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0859    0.0074    2.2224    2.2027    1.0000  296.0000    0.1388

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            5.1206    0.1057   48.4547    0.0000    4.9126    5.3286
condition_median   -0.2721    0.1833   -1.4842    0.1388   -0.6329    0.0887

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.3920    0.1537    2.7213   26.7838    2.0000  295.0000    0.0000

Model: 
                     coeff        se         t         p      LLCI      ULCI
constant            1.5474    0.3495    4.4275    0.0000    0.8595    2.2352
condition_median    0.0062    0.2036    0.0305    0.9757   -0.3946    0.4070
easy                0.4692    0.0643    7.2945    0.0000    0.3426    0.5957

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
     0.0062    0.2036    0.0305    0.9757   -0.3946    0.4070

Indirect effect(s) of X on Y:
        Effect    BootSE  BootLLCI  BootULCI
easy   -0.1277    0.0920   -0.3038    0.0520

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_average -> effective -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                          
  Model: 4                
      Y: purchase         
      X: condition_average
      M: effective        

Sample size: 298

Random seed: 3833


*********************************************************************** 
Outcome Variable: effective

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.1094    0.0120    1.3114    3.5839    1.0000  296.0000    0.0593

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             5.2060    0.0812   64.1294    0.0000    5.0463    5.3658
condition_average   -0.2666    0.1408   -1.8931    0.0593   -0.5438    0.0105

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.6260    0.3919    1.9552   95.0699    2.0000  295.0000    0.0000

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant            -1.0781    0.3825   -2.8182    0.0052   -1.8309   -0.3252
condition_average    0.0171    0.1730    0.0988    0.9214   -0.3234    0.3576
effective            0.9735    0.0710   13.7168    0.0000    0.8338    1.1132

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
     0.0171    0.1730    0.0988    0.9214   -0.3234    0.3576

Indirect effect(s) of X on Y:
             Effect    BootSE  BootLLCI  BootULCI
effective   -0.2596    0.1407   -0.5433    0.0187

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_average -> compare -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                          
  Model: 4                
      Y: purchase         
      X: condition_average
      M: compare          

Sample size: 298

Random seed: 748534


*********************************************************************** 
Outcome Variable: compare

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0826    0.0068    1.3891    2.0332    1.0000  296.0000    0.1549

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             5.0754    0.0835   60.7483    0.0000    4.9110    5.2398
condition_average   -0.2067    0.1450   -1.4259    0.1549   -0.4920    0.0786

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.6371    0.4059    1.9103  100.7798    2.0000  295.0000    0.0000

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant            -0.8966    0.3596   -2.4938    0.0132   -1.6042   -0.1890
condition_average   -0.0435    0.1706   -0.2549    0.7990   -0.3792    0.2922
compare              0.9628    0.0682   14.1253    0.0000    0.8287    1.0969

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
    -0.0435    0.1706   -0.2549    0.7990   -0.3792    0.2922

Indirect effect(s) of X on Y:
           Effect    BootSE  BootLLCI  BootULCI
compare   -0.1990    0.1405   -0.4763    0.0758

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_average -> maximum -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                          
  Model: 4                
      Y: purchase         
      X: condition_average
      M: maximum          

Sample size: 298

Random seed: 754472


*********************************************************************** 
Outcome Variable: maximum

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0722    0.0052    1.7267    1.5524    1.0000  296.0000    0.2138

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             5.1307    0.0932   55.0793    0.0000    4.9473    5.3140
condition_average   -0.2014    0.1616   -1.2459    0.2138   -0.5194    0.1167

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.5302    0.2811    2.3114   57.6882    2.0000  295.0000    0.0000

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             0.3110    0.3615    0.8603    0.3903   -0.4004    1.0224
condition_average   -0.0981    0.1875   -0.5232    0.6012   -0.4670    0.2709
maximum              0.7171    0.0672   10.6628    0.0000    0.5847    0.8494

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
    -0.0981    0.1875   -0.5232    0.6012   -0.4670    0.2709

Indirect effect(s) of X on Y:
           Effect    BootSE  BootLLCI  BootULCI
maximum   -0.1444    0.1172   -0.3856    0.0801

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_average -> trust -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                          
  Model: 4                
      Y: purchase         
      X: condition_average
      M: trust            

Sample size: 298

Random seed: 75013


*********************************************************************** 
Outcome Variable: trust

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0235    0.0006    2.1437    0.1632    1.0000  296.0000    0.6865

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             4.5980    0.1038   44.3012    0.0000    4.3937    4.8022
condition_average   -0.0727    0.1801   -0.4039    0.6865   -0.4271    0.2816

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.6571    0.4317    1.8273  112.0573    2.0000  295.0000    0.0000

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             0.3137    0.2647    1.1851    0.2369   -0.2072    0.8346
condition_average   -0.1843    0.1663   -1.1084    0.2686   -0.5116    0.1430
trust                0.7995    0.0537   14.8992    0.0000    0.6939    0.9051

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
    -0.1843    0.1663   -1.1084    0.2686   -0.5116    0.1430

Indirect effect(s) of X on Y:
         Effect    BootSE  BootLLCI  BootULCI
trust   -0.0582    0.1460   -0.3462    0.2235

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

==============================
Mediation: condition_average -> easy -> purchase


**************** PROCESS Procedure for R Version 5.0 ****************** 
 
           Written by Andrew F. Hayes, Ph.D.  www.afhayes.com              
   Documentation available in Hayes (2022). www.guilford.com/p/hayes3   
 
*********************************************************************** 
                          
  Model: 4                
      Y: purchase         
      X: condition_average
      M: easy             

Sample size: 298

Random seed: 616846


*********************************************************************** 
Outcome Variable: easy

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.0095    0.0001    2.2387    0.0268    1.0000  296.0000    0.8702

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             5.0402    0.1061   47.5195    0.0000    4.8315    5.2489
condition_average   -0.0301    0.1840   -0.1636    0.8702   -0.3923    0.3321

*********************************************************************** 
Outcome Variable: purchase

Model Summary: 
          R      R-sq       MSE         F       df1       df2         p
     0.3966    0.1573    2.7096   27.5350    2.0000  295.0000    0.0000

Model: 
                      coeff        se         t         p      LLCI      ULCI
constant             1.6296    0.3428    4.7542    0.0000    0.9550    2.3042
condition_average   -0.2284    0.2025   -1.1280    0.2602   -0.6268    0.1701
easy                 0.4683    0.0639    7.3236    0.0000    0.3425    0.5942

*********************************************************************** 
Bootstrapping progress:
  |>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>| 100%

**************** DIRECT AND INDIRECT EFFECTS OF X ON Y ****************

Direct effect of X on Y:
     effect        se         t         p      LLCI      ULCI
    -0.2284    0.2025   -1.1280    0.2602   -0.6268    0.1701

Indirect effect(s) of X on Y:
        Effect    BootSE  BootLLCI  BootULCI
easy   -0.0141    0.0831   -0.1824    0.1506

******************** ANALYSIS NOTES AND ERRORS ************************ 

Level of confidence for all confidence intervals in output: 95

Number of bootstraps for percentile bootstrap confidence intervals: 5000
NULL

Study 1 Analysis

Elaine Young

2026-03-03

Main Effects

Dependent Variable: Effective

Regression Estimates

Planned Contrasts

Dependent Variable: Compare

Regression Estimates

Planned Contrasts

Dependent Variable: Purchase

Regression Estimates

Planned Contrasts

Dependent Variable: Maximum

Regression Estimates

Planned Contrasts

Dependent Variable: Trust

Regression Estimates

Planned Contrasts

Dependent Variable: Easy

Regression Estimates

Planned Contrasts

Models with Demographic Covariates

Dependent Variable: Effective

Covariate: Age

Covariate: Gender

Covariate: Income

Dependent Variable: Compare

Covariate: Age

Covariate: Gender

Covariate: Income

Dependent Variable: Purchase

Covariate: Age

Covariate: Gender

Covariate: Income

Dependent Variable: Maximum

Covariate: Age

Covariate: Gender

Covariate: Income

Dependent Variable: Trust

Covariate: Age

Covariate: Gender

Covariate: Income

Dependent Variable: Easy

Covariate: Age

Covariate: Gender

Covariate: Income