AI Trust S2 - Item-level Analysis (3x2, no composites)

Valid entries and size of groups

There is a total of 394 entries in the dataset. 59 participants failed the attention check or the comprehension check. The valid number of entries is n = 335.

Cell counts (3 x 2 design):

ai_training	stakes	n	percentage
yes_ai	low	58	17.31%
yes_ai	high	58	17.31%
control	low	51	15.22%
control	high	55	16.42%
no_ai	low	58	17.31%
no_ai	high	55	16.42%

How to read this file

This is the item-level counterpart to the composite analysis. For each scale you get a Reliability diagnostics tab followed by a full 3x2 report for every individual item. When a composite’s α is below threshold in S2-analysis.Rmd, use the Reliability diagnostics here to find the offending item (look for a low or negative r.drop, or an alpha.drop row whose raw_alpha sits above the overall α), and use the per-item ANOVAs to check whether the items are telling a consistent story before you decide to drop or keep any of them.

Item-level analyses

Trust

Reliability diagnostics

Overall reliability

raw_alpha	std_alpha	avg_inter_item_r	n_items
0.931	0.934	0.876	2

Reliability if an item is dropped (raw_alpha rising above the overall value flags a problem item)

	raw_alpha	std.alpha	G6(smc)	average_r	S/N	alpha se	var.r	med.r
comfort	0.976	0.876	0.767	0.876	7.041	NA	0	0.876
confidence	0.786	0.876	0.767	0.876	7.041	NA	0	0.876

Item statistics – r.drop is the corrected item-total correlation (low / negative = weak item)

	n	raw.r	std.r	r.cor	r.drop	mean	sd
comfort	335	0.972	0.968	0.906	0.876	4.782	1.342
confidence	334	0.965	0.968	0.906	0.876	4.728	1.203

Comfort

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	comfort	58	4.241	1.615	0.212	0.425
high	yes_ai	comfort	58	3.759	1.647	0.216	0.433
low	control	comfort	51	5.157	0.731	0.102	0.206
high	control	comfort	55	4.709	1.165	0.157	0.315
low	no_ai	comfort	58	5.552	0.654	0.086	0.172
high	no_ai	comfort	55	5.345	0.821	0.111	0.222

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	comfort	116	4.000	1.642	0.152	0.302
control	comfort	106	4.925	1.002	0.097	0.193
no_ai	comfort	113	5.451	0.744	0.070	0.139

By stakes

stakes	variable	n	mean	sd	se	ci
low	comfort	167	4.976	1.232	0.095	0.188
high	comfort	168	4.589	1.420	0.110	0.216

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: comfort
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training        123.17   2 43.6571 < 2.2e-16 ***
## stakes              11.99   1  8.4965  0.003802 ** 
## ai_training:stakes   1.28   2  0.4535  0.635770    
## Residuals          464.11 329                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.21 | [0.15, 1.00]
## stakes             |           0.03 | [0.00, 1.00]
## ai_training:stakes |       2.75e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.52 | [0.41, Inf]
## stakes             |                0.16 | [0.07, Inf]
## ai_training:stakes |                0.05 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0000	****	0.0001	***	-0.7151	-1.03	-0.41	moderate
low	yes_ai	no_ai	58	58	0.0000	****	0.0000	****	-1.0638	-1.42	-0.77	large
low	control	no_ai	51	58	0.0641	ns	0.0641	ns	-0.5714	-1.01	-0.17	moderate
high	yes_ai	control	58	55	0.0001	****	0.0003	***	-0.6632	-1.06	-0.31	moderate
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-1.2095	-1.61	-0.86	large
high	control	no_ai	55	55	0.0092	**	0.0184	*	-0.6312	-1.02	-0.24	moderate

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.1140	ns	0.2280	ns	0.2960	-0.07	0.68	small
control	low	high	51	55	0.0208		0.0624	ns	0.4564	0.09	0.79	small
no_ai	low	high	58	55	0.1410	ns	0.2280	ns	0.2787	-0.06	0.66	small

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: comfort
##             Sum Sq  Df F value    Pr(>F)    
## ai_training 123.71   2  43.019 < 2.2e-16 ***
## Residuals   477.38 332                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.21 | [0.14, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.51 | [0.41, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: comfort
##           Sum Sq  Df F value   Pr(>F)   
## stakes     12.53   1  7.0879 0.008137 **
## Residuals 588.56 333                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter | Eta2 |       95% CI
## -------------------------------
## stakes    | 0.02 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.15 | [0.06, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.0000	****	0.0000	****	-0.6728	116	106	-0.91	-0.43	moderate
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-1.1337	116	113	-1.39	-0.91	large
control	no_ai	106	113	0.0013	**	0.0013	**	-0.5998	106	113	-0.86	-0.34	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.0081	**	0.0081	**	0.2909	167	168	0.08	0.51	small

Regression (exploratory)

Confidence

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	confidence	58	4.241	1.479	0.194	0.389
high	yes_ai	confidence	58	3.931	1.413	0.185	0.371
low	control	confidence	51	5.000	0.849	0.119	0.239
high	control	confidence	54	4.685	0.928	0.126	0.253
low	no_ai	confidence	58	5.276	0.790	0.104	0.208
high	no_ai	confidence	55	5.291	0.832	0.112	0.225

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	confidence	116	4.086	1.448	0.134	0.266
control	confidence	105	4.838	0.900	0.088	0.174
no_ai	confidence	113	5.283	0.807	0.076	0.150

By stakes

stakes	variable	n	mean	sd	se	ci
low	confidence	167	4.832	1.175	0.091	0.180
high	confidence	167	4.623	1.225	0.095	0.187

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: confidence
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         83.61   2 34.8974 1.816e-14 ***
## stakes               3.39   1  2.8339   0.09325 .  
## ai_training:stakes   2.00   2  0.8365   0.43415    
## Residuals          392.92 328                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.18 | [0.12, 1.00]
## stakes             |       8.57e-03 | [0.00, 1.00]
## ai_training:stakes |       5.07e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.46 | [0.36, Inf]
## stakes             |                0.09 | [0.00, Inf]
## ai_training:stakes |                0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0004	***	0.0015	**	-0.6192	-0.97	-0.30	moderate
low	yes_ai	no_ai	58	58	0.0000	****	0.0000	****	-0.8726	-1.23	-0.58	large
low	control	no_ai	51	58	0.1910	ns	0.1910	ns	-0.3373	-0.75	0.07	small
high	yes_ai	control	58	55	0.0004	***	0.0015	**	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-1.1657	-1.60	-0.82	large
high	control	no_ai	55	55	0.0044	**	0.0088	**	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.2500	ns	0.5000	ns	0.2146	-0.13	0.62	small
control	low	high	51	55	0.0731	ns	0.2193	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.9220	ns	0.9220	ns	-0.0186	-0.39	0.36	negligible

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: confidence
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  83.88   2  34.853 1.836e-14 ***
## Residuals   398.32 331                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.17 | [0.11, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.46 | [0.36, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: confidence
##           Sum Sq  Df F value Pr(>F)
## stakes      3.67   1  2.5445 0.1116
## Residuals 478.54 332               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 7.61e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.09 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.000	****	0.000	****	-0.6168	116	105	-0.87	-0.39	moderate
yes_ai	no_ai	116	113	0.000	****	0.000	****	-1.0176	116	113	-1.29	-0.79	large
control	no_ai	106	113	0.003	**	0.003	**	-0.5218	105	113	-0.82	-0.24	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.112	ns	0.112	ns	0.1746	167	167	-0.05	0.43	negligible

Regression (exploratory)

Ability

Reliability diagnostics

Overall reliability

raw_alpha	std_alpha	avg_inter_item_r	n_items
0.963	0.964	0.9	3

Reliability if an item is dropped (raw_alpha rising above the overall value flags a problem item)

	raw_alpha	std.alpha	G6(smc)	average_r	S/N	alpha se	var.r	med.r
ability1	0.948	0.949	0.902	0.902	18.431	0.006	NA	0.902
ability2	0.955	0.955	0.914	0.914	21.331	0.005	NA	0.914
ability3	0.935	0.938	0.883	0.883	15.138	0.007	NA	0.883

Item statistics – r.drop is the corrected item-total correlation (low / negative = weak item)

	n	raw.r	std.r	r.cor	r.drop	mean	sd
ability1	335	0.963	0.965	0.940	0.921	4.973	1.144
ability2	333	0.964	0.961	0.928	0.914	4.775	1.287
ability3	334	0.971	0.972	0.954	0.937	4.964	1.162

Ability1

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	ability1	58	4.466	1.404	0.184	0.369
high	yes_ai	ability1	58	4.138	1.492	0.196	0.392
low	control	ability1	51	5.216	0.757	0.106	0.213
high	control	ability1	55	5.018	0.680	0.092	0.184
low	no_ai	ability1	58	5.517	0.682	0.090	0.179
high	no_ai	ability1	55	5.545	0.662	0.089	0.179

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	ability1	116	4.302	1.452	0.135	0.267
control	ability1	106	5.113	0.721	0.070	0.139
no_ai	ability1	113	5.531	0.669	0.063	0.125

By stakes

stakes	variable	n	mean	sd	se	ci
low	ability1	167	5.060	1.101	0.085	0.168
high	ability1	168	4.887	1.181	0.091	0.180

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: ability1
##                    Sum Sq  Df F value Pr(>F)    
## ai_training         89.35   2 42.8437 <2e-16 ***
## stakes               2.32   1  2.2235 0.1369    
## ai_training:stakes   1.85   2  0.8863 0.4132    
## Residuals          343.06 329                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.21 | [0.14, 1.00]
## stakes             |       6.71e-03 | [0.00, 1.00]
## ai_training:stakes |       5.36e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.51 | [0.41, Inf]
## stakes             |                0.08 | [0.00, Inf]
## ai_training:stakes |                0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0002	***	0.0005	***	-0.6534	-0.99	-0.35	moderate
low	yes_ai	no_ai	58	58	0.0000	****	0.0000	****	-0.9528	-1.29	-0.66	large
low	control	no_ai	51	58	0.1220	ns	0.1220	ns	-0.4202	-0.83	-0.06	small
high	yes_ai	control	58	55	0.0000	****	0.0000	****	-0.7525	-1.14	-0.42	moderate
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-1.2087	-1.63	-0.90	large
high	control	no_ai	55	55	0.0081	**	0.0162	*	-0.7859	-1.28	-0.37	moderate

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.226	ns	0.480	ns	0.2261	-0.14	0.62	small
control	low	high	51	55	0.160	ns	0.480	ns	0.2751	-0.09	0.68	small
no_ai	low	high	58	55	0.824	ns	0.824	ns	-0.0420	-0.41	0.33	negligible

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: ability1
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  89.54   2  42.805 < 2.2e-16 ***
## Residuals   347.22 332                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.21 | [0.14, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.51 | [0.41, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: ability1
##           Sum Sq  Df F value Pr(>F)
## stakes      2.51   1  1.9216 0.1666
## Residuals 434.25 333               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 5.74e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.08 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.0000	****	0.0000	****	-0.6983	116	106	-0.94	-0.46	moderate
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-1.0828	116	113	-1.34	-0.86	large
control	no_ai	106	113	0.0027	**	0.0027	**	-0.6012	106	113	-0.89	-0.32	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.167	ns	0.167	ns	0.1515	167	168	-0.07	0.37	negligible

Regression (exploratory)

Ability2

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	ability2	58	4.241	1.537	0.202	0.404
high	yes_ai	ability2	57	3.842	1.677	0.222	0.445
low	control	ability2	51	5.059	0.835	0.117	0.235
high	control	ability2	55	4.709	0.896	0.121	0.242
low	no_ai	ability2	58	5.448	0.730	0.096	0.192
high	no_ai	ability2	54	5.407	0.765	0.104	0.209

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	ability2	115	4.043	1.613	0.150	0.298
control	ability2	106	4.877	0.881	0.086	0.170
no_ai	ability2	112	5.429	0.744	0.070	0.139

By stakes

stakes	variable	n	mean	sd	se	ci
low	ability2	167	4.910	1.212	0.094	0.185
high	ability2	166	4.639	1.349	0.105	0.207

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: ability2
##                    Sum Sq  Df F value  Pr(>F)    
## ai_training        110.10   2 41.6949 < 2e-16 ***
## stakes               5.75   1  4.3577 0.03762 *  
## ai_training:stakes   2.11   2  0.8001 0.45017    
## Residuals          431.75 327                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.20 | [0.14, 1.00]
## stakes             |           0.01 | [0.00, 1.00]
## ai_training:stakes |       4.87e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.50 | [0.40, Inf]
## stakes             |                0.12 | [0.02, Inf]
## ai_training:stakes |                0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0002	***	0.0007	***	-0.6496	-0.97	-0.31	moderate
low	yes_ai	no_ai	58	58	0.0000	****	0.0000	****	-1.0033	-1.32	-0.70	large
low	control	no_ai	51	58	0.0679	ns	0.0679	ns	-0.4990	-0.94	-0.14	small
high	yes_ai	control	58	55	0.0002	***	0.0007	***	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	NA	NA	NA	NA
high	control	no_ai	55	55	0.0026	**	0.0052	**	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.1860	ns	0.3720	ns	NA	NA	NA	NA
control	low	high	51	55	0.0404		0.1212	ns	0.4034	0.02	0.79	small
no_ai	low	high	58	55	0.7730	ns	0.7730	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: ability2
##             Sum Sq  Df F value    Pr(>F)    
## ai_training 110.49   2   41.47 < 2.2e-16 ***
## Residuals   439.62 330                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.20 | [0.14, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.50 | [0.40, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: ability2
##           Sum Sq  Df F value  Pr(>F)  
## stakes      6.14   1  3.7375 0.05406 .
## Residuals 543.97 331                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter | Eta2 |       95% CI
## -------------------------------
## stakes    | 0.01 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.11 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0e+00	****	0e+00	****	-0.6346	115	106	-0.87	-0.40	moderate
yes_ai	no_ai	116	113	0e+00	****	0e+00	****	-1.0977	115	112	-1.37	-0.88	large
control	no_ai	106	113	5e-04	***	5e-04	***	-0.6778	106	112	-0.98	-0.42	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.0541	ns	0.0541	ns	0.2119	167	166	-0.0097	0.42	small

Regression (exploratory)

Ability3

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	ability3	58	4.448	1.379	0.181	0.363
high	yes_ai	ability3	58	4.138	1.480	0.194	0.389
low	control	ability3	51	5.216	0.730	0.102	0.205
high	control	ability3	55	4.964	0.881	0.119	0.238
low	no_ai	ability3	58	5.569	0.652	0.086	0.171
high	no_ai	ability3	54	5.519	0.720	0.098	0.197

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	ability3	116	4.293	1.433	0.133	0.263
control	ability3	106	5.085	0.818	0.079	0.158
no_ai	ability3	112	5.545	0.683	0.065	0.128

By stakes

stakes	variable	n	mean	sd	se	ci
low	ability3	167	5.072	1.090	0.084	0.166
high	ability3	167	4.856	1.224	0.095	0.187

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: ability3
##                    Sum Sq  Df F value  Pr(>F)    
## ai_training         91.14   2 42.2819 < 2e-16 ***
## stakes               3.50   1  3.2447 0.07257 .  
## ai_training:stakes   1.05   2  0.4864 0.61530    
## Residuals          353.50 328                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.20 | [0.14, 1.00]
## stakes             |       9.80e-03 | [0.00, 1.00]
## ai_training:stakes |       2.96e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.51 | [0.41, Inf]
## stakes             |                0.10 | [0.00, Inf]
## ai_training:stakes |                0.05 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0001	****	0.0003	***	-0.6833	-1.03	-0.38	moderate
low	yes_ai	no_ai	58	58	0.0000	****	0.0000	****	-1.0392	-1.41	-0.74	large
low	control	no_ai	51	58	0.0636	ns	0.0636	ns	-0.5125	-0.93	-0.14	moderate
high	yes_ai	control	58	55	0.0001	****	0.0003	***	-0.6735	-1.04	-0.35	moderate
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	NA	NA	NA	NA
high	control	no_ai	55	55	0.0086	**	0.0171	*	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.245	ns	0.490	ns	0.2170	-0.15	0.62	small
control	low	high	51	55	0.113	ns	0.339	ns	0.3104	-0.09	0.69	small
no_ai	low	high	58	55	0.698	ns	0.698	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: ability3
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  91.52   2  42.304 < 2.2e-16 ***
## Residuals   358.05 331                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.20 | [0.14, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.51 | [0.41, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: ability3
##           Sum Sq  Df F value  Pr(>F)  
## stakes      3.88   1  2.8904 0.09004 .
## Residuals 445.69 332                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 8.63e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.09 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.0000	****	0.0000	****	-0.6711	116	106	-0.93	-0.44	moderate
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-1.1090	116	112	-1.35	-0.87	large
control	no_ai	106	113	0.0012	**	0.0012	**	-0.6117	106	112	-0.88	-0.32	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.09	ns	0.09	ns	0.1861	167	167	-0.03	0.4	negligible

Regression (exploratory)

Benevolence

Reliability diagnostics

Overall reliability

raw_alpha	std_alpha	avg_inter_item_r	n_items
0.889	0.889	0.728	3

Reliability if an item is dropped (raw_alpha rising above the overall value flags a problem item)

	raw_alpha	std.alpha	G6(smc)	average_r	S/N	alpha se	var.r	med.r
benevolence1	0.827	0.828	0.707	0.707	4.818	0.019	NA	0.707
benevolence2	0.891	0.892	0.806	0.806	8.300	0.012	NA	0.806
benevolence3	0.801	0.803	0.671	0.671	4.076	0.022	NA	0.671

Item statistics – r.drop is the corrected item-total correlation (low / negative = weak item)

	n	raw.r	std.r	r.cor	r.drop	mean	sd
benevolence1	331	0.913	0.913	0.858	0.799	4.637	1.121
benevolence2	333	0.874	0.876	0.762	0.724	4.916	1.103
benevolence3	333	0.928	0.926	0.884	0.828	4.559	1.164

Benevolence1

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	benevolence1	57	4.579	1.253	0.166	0.332
high	yes_ai	benevolence1	58	4.190	1.067	0.140	0.281
low	control	benevolence1	50	4.520	1.054	0.149	0.300
high	control	benevolence1	55	4.382	1.163	0.157	0.314
low	no_ai	benevolence1	57	4.947	0.990	0.131	0.263
high	no_ai	benevolence1	54	5.222	0.861	0.117	0.235

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	benevolence1	115	4.383	1.174	0.109	0.217
control	benevolence1	105	4.448	1.109	0.108	0.215
no_ai	benevolence1	111	5.081	0.936	0.089	0.176

By stakes

stakes	variable	n	mean	sd	se	ci
low	benevolence1	164	4.689	1.116	0.087	0.172
high	benevolence1	167	4.587	1.126	0.087	0.172

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence1
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         32.86   2 14.2600 1.158e-06 ***
## stakes               0.63   1  0.5426    0.4619    
## ai_training:stakes   6.33   2  2.7455    0.0657 .  
## Residuals          374.45 325                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.08 | [0.04, 1.00]
## stakes             |       1.67e-03 | [0.00, 1.00]
## ai_training:stakes |           0.02 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.30 | [0.20, Inf]
## stakes             |                0.04 | [0.00, Inf]
## ai_training:stakes |                0.13 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.7840	ns	0.7840	ns	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0.0774	ns	0.2322	ns	NA	NA	NA	NA
low	control	no_ai	51	58	0.0480		0.1920	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.3270	ns	0.6540	ns	-0.1724	-0.53	0.22	negligible
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	NA	NA	NA	NA
high	control	no_ai	55	55	0.0000	****	0.0002	***	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.0753	ns	0.2259	ns	NA	NA	NA	NA
control	low	high	51	55	0.5260	ns	0.5260	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.1220	ns	0.2440	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence1
##             Sum Sq  Df F value    Pr(>F)    
## ai_training   33.1   2  14.232 1.182e-06 ***
## Residuals    381.4 328                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.08 | [0.04, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.29 | [0.20, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence1
##           Sum Sq  Df F value Pr(>F)
## stakes      0.86   1  0.6874 0.4077
## Residuals 413.63 329               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 2.08e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.05 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.655	ns	0.655	ns	-0.0568	115	105	-0.33	0.20	negligible
yes_ai	no_ai	116	113	0.000	****	0.000	****	-0.6567	115	111	-0.94	-0.38	moderate
control	no_ai	106	113	0.000	****	0.000	****	-0.6188	105	111	-0.92	-0.35	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.408	ns	0.408	ns	0.0911	164	167	-0.13	0.32	negligible

Regression (exploratory)

Benevolence2

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	benevolence2	58	4.759	1.302	0.171	0.342
high	yes_ai	benevolence2	58	4.828	0.976	0.128	0.257
low	control	benevolence2	51	4.725	1.133	0.159	0.319
high	control	benevolence2	55	4.745	1.220	0.165	0.330
low	no_ai	benevolence2	57	5.193	0.972	0.129	0.258
high	no_ai	benevolence2	54	5.241	0.867	0.118	0.237

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	benevolence2	116	4.793	1.146	0.106	0.211
control	benevolence2	106	4.736	1.174	0.114	0.226
no_ai	benevolence2	111	5.216	0.919	0.087	0.173

By stakes

stakes	variable	n	mean	sd	se	ci
low	benevolence2	166	4.898	1.158	0.090	0.177
high	benevolence2	167	4.934	1.048	0.081	0.160

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence2
##                    Sum Sq  Df F value   Pr(>F)   
## ai_training         15.26   2  6.4281 0.001827 **
## stakes               0.18   1  0.1503 0.698526   
## ai_training:stakes   0.03   2  0.0140 0.986070   
## Residuals          388.24 327                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.04 | [0.01, 1.00]
## stakes             |       4.59e-04 | [0.00, 1.00]
## ai_training:stakes |       8.58e-05 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.20 | [0.10, Inf]
## stakes             |                0.02 | [0.00, Inf]
## ai_training:stakes |            9.26e-03 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.8800	ns	1.0000	ns	0.0270	-0.34	0.40	negligible
low	yes_ai	no_ai	58	58	0.0436		0.1785	ns	NA	NA	NA	NA
low	control	no_ai	51	58	0.0357		0.1785	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.6730	ns	1.0000	ns	0.0746	-0.30	0.43	negligible
high	yes_ai	no_ai	58	55	0.0357		0.1785	ns	NA	NA	NA	NA
high	control	no_ai	55	55	0.0132		0.0792	ns	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.747	ns	1	ns	-0.0599	-0.40	0.35	negligible
control	low	high	51	55	0.931	ns	1	ns	-0.0169	-0.42	0.34	negligible
no_ai	low	high	58	55	0.786	ns	1	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence2
##             Sum Sq  Df F value   Pr(>F)   
## ai_training  15.20   2   6.455 0.001779 **
## Residuals   388.45 330                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.04 | [0.01, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.20 | [0.10, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence2
##           Sum Sq  Df F value Pr(>F)
## stakes      0.11   1  0.0912 0.7629
## Residuals 403.53 331               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 2.75e-04 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.02 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.6950	ns	0.6950	ns	0.0494	116	106	-0.22	0.33	negligible
yes_ai	no_ai	116	113	0.0036	**	0.0071	**	-0.4064	116	111	-0.68	-0.12	small
control	no_ai	106	113	0.0012	**	0.0037	**	-0.4571	106	111	-0.74	-0.20	small

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.763	ns	0.763	ns	-0.0331	166	167	-0.25	0.17	negligible

Regression (exploratory)

Benevolence3

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	benevolence3	57	4.351	1.356	0.180	0.360
high	yes_ai	benevolence3	58	4.121	1.093	0.144	0.288
low	control	benevolence3	51	4.510	1.120	0.157	0.315
high	control	benevolence3	55	4.400	1.099	0.148	0.297
low	no_ai	benevolence3	57	4.912	1.057	0.140	0.280
high	no_ai	benevolence3	55	5.073	0.979	0.132	0.265

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	benevolence3	115	4.235	1.231	0.115	0.227
control	benevolence3	106	4.453	1.105	0.107	0.213
no_ai	benevolence3	112	4.991	1.018	0.096	0.191

By stakes

stakes	variable	n	mean	sd	se	ci
low	benevolence3	165	4.594	1.204	0.094	0.185
high	benevolence3	168	4.524	1.126	0.087	0.172

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence3
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         34.09   2 13.4829 2.362e-06 ***
## stakes               0.30   1  0.2408    0.6240    
## ai_training:stakes   2.26   2  0.8934    0.4103    
## Residuals          413.35 327                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.08 | [0.03, 1.00]
## stakes             |       7.36e-04 | [0.00, 1.00]
## ai_training:stakes |       5.43e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.29 | [0.19, Inf]
## stakes             |                0.03 | [0.00, Inf]
## ai_training:stakes |                0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.4880	ns	0.4880	ns	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0.0125		0.0500	*	NA	NA	NA	NA
low	control	no_ai	51	58	0.0805	ns	0.2415	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.1630	ns	0.3260	ns	-0.2548	-0.63	0.12	small
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-0.9162	-1.35	-0.54	large
high	control	no_ai	55	55	0.0011	**	0.0053	**	-0.6466	-1.09	-0.27	moderate

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.318	ns	0.954	ns	NA	NA	NA	NA
control	low	high	51	55	0.612	ns	0.954	ns	0.099	-0.29	0.52	negligible
no_ai	low	high	58	55	0.407	ns	0.954	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence3
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  34.19   2  13.565 2.181e-06 ***
## Residuals   415.92 330                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.08 | [0.03, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.29 | [0.19, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: benevolence3
##           Sum Sq  Df F value Pr(>F)
## stakes      0.41   1  0.3013 0.5834
## Residuals 449.70 331               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 9.10e-04 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.03 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.1500	ns	0.1500	ns	-0.1860	115	106	-0.46	0.05	negligible
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-0.6689	115	112	-0.97	-0.41	moderate
control	no_ai	106	113	0.0005	***	0.0009	***	-0.5072	106	112	-0.83	-0.23	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.583	ns	0.583	ns	0.0602	165	168	-0.14	0.25	negligible

Regression (exploratory)

Integrity

Reliability diagnostics

Overall reliability

raw_alpha	std_alpha	avg_inter_item_r	n_items
0.88	0.884	0.717	3

Reliability if an item is dropped (raw_alpha rising above the overall value flags a problem item)

	raw_alpha	std.alpha	G6(smc)	average_r	S/N	alpha se	var.r	med.r
integrity1	0.865	0.872	0.773	0.773	6.830	0.015	NA	0.773
integrity2	0.809	0.813	0.685	0.685	4.358	0.021	NA	0.685
integrity3	0.817	0.817	0.691	0.691	4.477	0.020	NA	0.691

Item statistics – r.drop is the corrected item-total correlation (low / negative = weak item)

	n	raw.r	std.r	r.cor	r.drop	mean	sd
integrity1	334	0.885	0.880	0.772	0.731	4.000	1.240
integrity2	334	0.911	0.912	0.853	0.792	4.566	1.170
integrity3	332	0.908	0.910	0.849	0.784	4.563	1.155

Integrity1

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	integrity1	58	3.569	1.216	0.160	0.320
high	yes_ai	integrity1	58	3.276	1.196	0.157	0.315
low	control	integrity1	51	4.078	1.093	0.153	0.307
high	control	integrity1	55	3.691	0.998	0.135	0.270
low	no_ai	integrity1	57	4.667	0.951	0.126	0.252
high	no_ai	integrity1	55	4.764	1.201	0.162	0.325

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	integrity1	116	3.422	1.210	0.112	0.222
control	integrity1	106	3.877	1.057	0.103	0.204
no_ai	integrity1	112	4.714	1.077	0.102	0.202

By stakes

stakes	variable	n	mean	sd	se	ci
low	integrity1	166	4.102	1.179	0.091	0.181
high	integrity1	168	3.899	1.293	0.100	0.197

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity1
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         97.06   2 39.0289 6.236e-16 ***
## stakes               3.08   1  2.4796    0.1163    
## ai_training:stakes   3.65   2  1.4659    0.2324    
## Residuals          407.84 328                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.19 | [0.13, 1.00]
## stakes             |       7.50e-03 | [0.00, 1.00]
## ai_training:stakes |       8.86e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.49 | [0.39, Inf]
## stakes             |                0.09 | [0.00, Inf]
## ai_training:stakes |                0.09 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0162		0.0324	*	-0.4393	-0.84	-0.0600	small
low	yes_ai	no_ai	58	58	0.0000	****	0.0000	****	NA	NA	NA	NA
low	control	no_ai	51	58	0.0058	**	0.0175	*	NA	NA	NA	NA
high	yes_ai	control	58	55	0.0541	ns	0.0541	ns	-0.3759	-0.75	-0.0057	small
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-1.2411	-1.71	-0.8800	large
high	control	no_ai	55	55	0.0000	****	0.0000	****	-0.9715	-1.51	-0.5900	large

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.193	ns	0.386	ns	0.2430	-0.1400	0.61	small
control	low	high	51	55	0.059	ns	0.177	ns	0.3711	-0.0077	0.75	small
no_ai	low	high	58	55	0.636	ns	0.636	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity1
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  97.44   2  38.898 6.719e-16 ***
## Residuals   414.56 331                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.19 | [0.13, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.48 | [0.39, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity1
##           Sum Sq  Df F value Pr(>F)
## stakes      3.46   1  2.2596 0.1337
## Residuals 508.54 332               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 6.76e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.08 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.0027	**	0.0027	**	-0.3992	116	106	-0.67	-0.13	small
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-1.1266	116	112	-1.44	-0.82	large
control	no_ai	106	113	0.0000	****	0.0000	****	-0.7838	106	112	-1.10	-0.50	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.134	ns	0.134	ns	0.1645	166	168	-0.07	0.39	negligible

Regression (exploratory)

Integrity2

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	integrity2	58	4.103	1.423	0.187	0.374
high	yes_ai	integrity2	58	3.983	1.221	0.160	0.321
low	control	integrity2	51	4.647	0.976	0.137	0.275
high	control	integrity2	55	4.473	0.959	0.129	0.259
low	no_ai	integrity2	57	5.053	0.915	0.121	0.243
high	no_ai	integrity2	55	5.182	0.905	0.122	0.245

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	integrity2	116	4.043	1.321	0.123	0.243
control	integrity2	106	4.557	0.967	0.094	0.186
no_ai	integrity2	112	5.116	0.908	0.086	0.170

By stakes

stakes	variable	n	mean	sd	se	ci
low	integrity2	166	4.596	1.196	0.093	0.183
high	integrity2	168	4.536	1.147	0.089	0.175

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity2
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         65.55   2 27.6538 7.971e-12 ***
## stakes               0.24   1  0.2045    0.6514    
## ai_training:stakes   1.45   2  0.6123    0.5427    
## Residuals          388.74 328                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.14 | [0.09, 1.00]
## stakes             |       6.23e-04 | [0.00, 1.00]
## ai_training:stakes |       3.72e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.41 | [0.31, Inf]
## stakes             |                0.02 | [0.00, Inf]
## ai_training:stakes |                0.06 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0136		0.0402	*	-0.4404	-0.82	-0.09	small
low	yes_ai	no_ai	58	58	0.0000	****	0.0001	****	NA	NA	NA	NA
low	control	no_ai	51	58	0.0655	ns	0.0655	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.0134		0.0402	*	-0.4448	-0.82	-0.10	small
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-1.1116	-1.56	-0.75	large
high	control	no_ai	55	55	0.0005	***	0.0019	**	-0.7605	-1.21	-0.38	moderate

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.625	ns	1	ns	0.0910	-0.28	0.47	negligible
control	low	high	51	55	0.356	ns	1	ns	0.1802	-0.18	0.60	negligible
no_ai	low	high	58	55	0.454	ns	1	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity2
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  65.61   2  27.813 6.836e-12 ***
## Residuals   390.44 331                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.14 | [0.09, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.41 | [0.31, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity2
##           Sum Sq  Df F value Pr(>F)
## stakes      0.31   1  0.2239 0.6364
## Residuals 455.74 332               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 6.74e-04 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.03 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	5e-04	***	5e-04	***	-0.4405	116	106	-0.72	-0.17	small
yes_ai	no_ai	116	113	0e+00	****	0e+00	****	-0.9435	116	112	-1.22	-0.68	large
control	no_ai	106	113	2e-04	***	3e-04	***	-0.5971	106	112	-0.88	-0.33	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.636	ns	0.636	ns	0.0518	166	168	-0.16	0.27	negligible

Regression (exploratory)

Integrity3

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	integrity3	57	4.246	1.243	0.165	0.330
high	yes_ai	integrity3	57	3.912	1.154	0.153	0.306
low	control	integrity3	51	4.706	0.986	0.138	0.277
high	control	integrity3	55	4.273	1.096	0.148	0.296
low	no_ai	integrity3	57	5.000	0.906	0.120	0.240
high	no_ai	integrity3	55	5.273	0.932	0.126	0.252

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	integrity3	114	4.079	1.206	0.113	0.224
control	integrity3	106	4.481	1.062	0.103	0.205
no_ai	integrity3	112	5.134	0.925	0.087	0.173

By stakes

stakes	variable	n	mean	sd	se	ci
low	integrity3	165	4.648	1.098	0.085	0.169
high	integrity3	167	4.479	1.207	0.093	0.184

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity3
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         63.69   2 28.2455 4.866e-12 ***
## stakes               2.14   1  1.8995   0.16908    
## ai_training:stakes   8.07   2  3.5800   0.02898 *  
## Residuals          367.53 326                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.15 | [0.09, 1.00]
## stakes             |       5.79e-03 | [0.00, 1.00]
## ai_training:stakes |           0.02 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.42 | [0.32, Inf]
## stakes             |                0.08 | [0.00, Inf]
## ai_training:stakes |                0.15 | [0.03, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.0253		0.0759	ns	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0.0002	***	0.0008	***	NA	NA	NA	NA
low	control	no_ai	51	58	0.1510	ns	0.1510	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.0755	ns	0.1510	ns	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	NA	NA	NA	NA
high	control	no_ai	55	55	0.0000	****	0.0000	****	-0.9828	-1.46	-0.59	large

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.1410	ns	0.2380	ns	NA	NA	NA	NA
control	low	high	51	55	0.0353		0.1059	ns	0.4146	0.06	0.84	small
no_ai	low	high	58	55	0.1190	ns	0.2380	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity3
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  63.93   2   27.84 6.759e-12 ***
## Residuals   377.74 329                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.14 | [0.09, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.41 | [0.31, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: integrity3
##           Sum Sq  Df F value Pr(>F)
## stakes      2.38   1  1.7901 0.1818
## Residuals 439.29 330               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 5.40e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.0057	**	0.0057	**	-0.3531	114	106	-0.62	-0.08	small
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-0.9806	114	112	-1.28	-0.71	large
control	no_ai	106	113	0.0000	****	0.0000	****	-0.6567	106	112	-0.95	-0.39	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.182	ns	0.182	ns	0.1469	165	167	-0.07	0.36	negligible

Regression (exploratory)

Autonomy

Reliability diagnostics

Overall reliability

raw_alpha	std_alpha	avg_inter_item_r	n_items
0.872	0.874	0.698	3

Reliability if an item is dropped (raw_alpha rising above the overall value flags a problem item)

	raw_alpha	std.alpha	G6(smc)	average_r	S/N	alpha se	var.r	med.r
autonomy1	0.791	0.804	0.672	0.672	4.090	0.022	NA	0.672
autonomy2	0.875	0.878	0.782	0.782	7.169	0.013	NA	0.782
autonomy3	0.778	0.782	0.642	0.642	3.586	0.024	NA	0.642

Item statistics – r.drop is the corrected item-total correlation (low / negative = weak item)

	n	raw.r	std.r	r.cor	r.drop	mean	sd
autonomy1	332	0.908	0.904	0.843	0.787	4.346	1.435
autonomy2	333	0.847	0.863	0.736	0.696	4.480	1.265
autonomy3	332	0.927	0.915	0.865	0.806	4.193	1.589

Autonomy1

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	autonomy1	58	3.500	1.657	0.218	0.436
high	yes_ai	autonomy1	58	3.121	1.403	0.184	0.369
low	control	autonomy1	51	4.529	1.065	0.149	0.300
high	control	autonomy1	54	4.407	0.981	0.134	0.268
low	no_ai	autonomy1	57	5.333	0.690	0.091	0.183
high	no_ai	autonomy1	54	5.296	0.903	0.123	0.247

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	autonomy1	116	3.310	1.540	0.143	0.283
control	autonomy1	105	4.467	1.020	0.100	0.197
no_ai	autonomy1	111	5.315	0.798	0.076	0.150

By stakes

stakes	variable	n	mean	sd	se	ci
low	autonomy1	166	4.446	1.429	0.111	0.219
high	autonomy1	166	4.247	1.437	0.112	0.220

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy1
##                    Sum Sq  Df F value Pr(>F)    
## ai_training        229.76   2 83.9080 <2e-16 ***
## stakes               2.79   1  2.0414 0.1540    
## ai_training:stakes   1.81   2  0.6595 0.5178    
## Residuals          446.32 326                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.34 | [0.27, 1.00]
## stakes             |       6.22e-03 | [0.00, 1.00]
## ai_training:stakes |       4.03e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.72 | [0.61, Inf]
## stakes             |                0.08 | [0.00, Inf]
## ai_training:stakes |                0.06 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0e+00	****	1e-04	****	-0.7293	-1.12	-0.37	moderate
low	yes_ai	no_ai	58	58	0e+00	****	0e+00	****	NA	NA	NA	NA
low	control	no_ai	51	58	7e-04	***	7e-04	***	NA	NA	NA	NA
high	yes_ai	control	58	55	0e+00	****	0e+00	****	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0e+00	****	0e+00	****	NA	NA	NA	NA
high	control	no_ai	55	55	1e-04	****	1e-04	***	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.186	ns	0.558	ns	0.2471	-0.14	0.66	small
control	low	high	51	55	0.543	ns	1.000	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.808	ns	1.000	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy1
##             Sum Sq  Df F value    Pr(>F)    
## ai_training 230.24   2  83.993 < 2.2e-16 ***
## Residuals   450.92 329                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.34 | [0.27, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.71 | [0.61, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy1
##           Sum Sq  Df F value Pr(>F)
## stakes      3.28   1  1.5968 0.2073
## Residuals 677.89 330               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 4.82e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0	****	0	****	-0.8767	116	105	-1.16	-0.61	large
yes_ai	no_ai	116	113	0	****	0	****	-1.6244	116	111	-1.91	-1.33	large
control	no_ai	106	113	0	****	0	****	-0.9303	105	111	-1.24	-0.64	large

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.207	ns	0.207	ns	0.1387	166	166	-0.07	0.36	negligible

Regression (exploratory)

Autonomy2

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	autonomy2	58	4.207	1.484	0.195	0.390
high	yes_ai	autonomy2	58	3.741	1.222	0.160	0.321
low	control	autonomy2	51	4.549	1.119	0.157	0.315
high	control	autonomy2	54	4.222	1.127	0.153	0.308
low	no_ai	autonomy2	57	4.965	1.017	0.135	0.270
high	no_ai	autonomy2	55	5.236	0.942	0.127	0.255

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	autonomy2	116	3.974	1.373	0.128	0.253
control	autonomy2	105	4.381	1.130	0.110	0.219
no_ai	autonomy2	112	5.098	0.986	0.093	0.185

By stakes

stakes	variable	n	mean	sd	se	ci
low	autonomy2	166	4.572	1.262	0.098	0.193
high	autonomy2	167	4.389	1.265	0.098	0.193

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy2
##                    Sum Sq  Df F value    Pr(>F)    
## ai_training         73.25   2 26.8241 1.633e-11 ***
## stakes               2.52   1  1.8436   0.17546    
## ai_training:stakes   8.63   2  3.1608   0.04369 *  
## Residuals          446.46 327                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.14 | [0.09, 1.00]
## stakes             |       5.61e-03 | [0.00, 1.00]
## ai_training:stakes |           0.02 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.41 | [0.31, Inf]
## stakes             |                0.08 | [0.00, Inf]
## ai_training:stakes |                0.14 | [0.02, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.1490	ns	0.1618	ns	-0.2580	-0.60	0.10	small
low	yes_ai	no_ai	58	58	0.0012	**	0.0046	**	NA	NA	NA	NA
low	control	no_ai	51	58	0.0809	ns	0.1618	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.0227		0.0681	ns	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0.0000	****	0.0000	****	-1.3655	-1.89	-0.92	large
high	control	no_ai	55	55	0.0000	****	0.0000	****	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.0677	ns	0.2031	ns	0.3425	-0.04	0.74	small
control	low	high	51	55	0.1390	ns	0.2780	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.1460	ns	0.2780	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy2
##             Sum Sq  Df F value    Pr(>F)    
## ai_training  73.52   2  26.509 2.107e-11 ***
## Residuals   457.60 330                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.14 | [0.08, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.40 | [0.30, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy2
##           Sum Sq  Df F value Pr(>F)
## stakes      2.79   1  1.7479 0.1871
## Residuals 528.33 331               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 5.25e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.07 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.0108		0.0108	*	-0.3219	116	105	-0.60	-0.05	small
yes_ai	no_ai	116	113	0.0000	****	0.0000	****	-0.9376	116	112	-1.23	-0.67	large
control	no_ai	106	113	0.0000	****	0.0000	****	-0.6779	105	112	-0.98	-0.41	moderate

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.187	ns	0.187	ns	0.1449	166	167	-0.05	0.37	negligible

Regression (exploratory)

Autonomy3

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	autonomy3	56	3.250	1.587	0.212	0.425
high	yes_ai	autonomy3	58	2.776	1.545	0.203	0.406
low	control	autonomy3	51	4.176	1.090	0.153	0.307
high	control	autonomy3	55	4.073	1.052	0.142	0.284
low	no_ai	autonomy3	57	5.404	1.033	0.137	0.274
high	no_ai	autonomy3	55	5.527	0.790	0.107	0.214

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	autonomy3	114	3.009	1.577	0.148	0.293
control	autonomy3	106	4.123	1.066	0.104	0.205
no_ai	autonomy3	112	5.464	0.920	0.087	0.172

By stakes

stakes	variable	n	mean	sd	se	ci
low	autonomy3	164	4.287	1.546	0.121	0.238
high	autonomy3	168	4.101	1.629	0.126	0.248

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy3
##                    Sum Sq  Df  F value Pr(>F)    
## ai_training        340.53   2 113.9439 <2e-16 ***
## stakes               1.97   1   1.3198 0.2515    
## ai_training:stakes   5.15   2   1.7220 0.1803    
## Residuals          487.14 326                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.41 | [0.35, 1.00]
## stakes             |       4.03e-03 | [0.00, 1.00]
## ai_training:stakes |           0.01 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.84 | [0.73, Inf]
## stakes             |                0.06 | [0.00, Inf]
## ai_training:stakes |                0.10 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	2e-04	***	2e-04	***	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0e+00	****	0e+00	****	NA	NA	NA	NA
low	control	no_ai	51	58	0e+00	****	0e+00	****	NA	NA	NA	NA
high	yes_ai	control	58	55	0e+00	****	0e+00	****	-0.9765	-1.40	-0.61	large
high	yes_ai	no_ai	58	55	0e+00	****	0e+00	****	-2.2246	-2.96	-1.74	large
high	control	no_ai	55	55	0e+00	****	0e+00	****	-1.5640	-2.23	-1.06	large

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.109	ns	0.327	ns	NA	NA	NA	NA
control	low	high	51	55	0.619	ns	0.958	ns	0.0969	-0.32	0.48	negligible
no_ai	low	high	58	55	0.479	ns	0.958	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy3
##             Sum Sq  Df F value    Pr(>F)    
## ai_training 341.41   2  113.63 < 2.2e-16 ***
## Residuals   494.25 329                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.41 | [0.34, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.83 | [0.72, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: autonomy3
##           Sum Sq  Df F value Pr(>F)
## stakes      2.85   1  1.1303 0.2885
## Residuals 832.81 330               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 3.41e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.06 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0	****	0	****	-0.8219	114	106	-1.09	-0.56	large
yes_ai	no_ai	116	113	0	****	0	****	-1.8982	114	112	-2.36	-1.53	large
control	no_ai	106	113	0	****	0	****	-1.3502	106	112	-1.80	-0.96	large

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.288	ns	0.288	ns	0.1167	164	168	-0.1	0.33	negligible

Regression (exploratory)

AI attitudes

Reliability diagnostics

Overall reliability

raw_alpha	std_alpha	avg_inter_item_r	n_items
0.978	0.976	0.954	2

Reliability if an item is dropped (raw_alpha rising above the overall value flags a problem item)

	raw_alpha	std.alpha	G6(smc)	average_r	S/N	alpha se	var.r	med.r
ai_attitude	0.957	0.954	0.909	0.954	20.544	NA	0	0.954
ai_feeling	0.955	0.954	0.909	0.954	20.544	NA	0	0.954

Item statistics – r.drop is the corrected item-total correlation (low / negative = weak item)

	n	raw.r	std.r	r.cor	r.drop	mean	sd
ai_attitude	331	0.988	0.988	0.965	0.956	3.115	1.698
ai_feeling	329	0.988	0.988	0.965	0.956	3.100	1.696

Ai Attitude

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	ai_attitude	57	3.439	1.690	0.224	0.449
high	yes_ai	ai_attitude	58	3.086	1.931	0.254	0.508
low	control	ai_attitude	50	3.340	1.698	0.240	0.482
high	control	ai_attitude	54	3.222	1.538	0.209	0.420
low	no_ai	ai_attitude	57	2.965	1.762	0.233	0.468
high	no_ai	ai_attitude	55	2.655	1.468	0.198	0.397

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	ai_attitude	115	3.261	1.817	0.169	0.336
control	ai_attitude	104	3.279	1.610	0.158	0.313
no_ai	ai_attitude	112	2.812	1.625	0.154	0.304

By stakes

stakes	variable	n	mean	sd	se	ci
low	ai_attitude	164	3.244	1.720	0.134	0.265
high	ai_attitude	167	2.988	1.672	0.129	0.255

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_attitude
##                    Sum Sq  Df F value  Pr(>F)  
## ai_training         15.86   2  2.7721 0.06401 .
## stakes               5.79   1  2.0232 0.15587  
## ai_training:stakes   0.84   2  0.1468 0.86351  
## Residuals          929.52 325                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.02 | [0.00, 1.00]
## stakes             |       6.19e-03 | [0.00, 1.00]
## ai_training:stakes |       9.03e-04 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.13 | [0.00, Inf]
## stakes             |                0.08 | [0.00, Inf]
## ai_training:stakes |                0.03 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.7670	ns	1.0000	ns	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0.1430	ns	0.7150	ns	NA	NA	NA	NA
low	control	no_ai	51	58	0.2620	ns	0.7860	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.6660	ns	1.0000	ns	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0.1700	ns	0.7150	ns	0.2507	-0.09	0.62	small
high	control	no_ai	55	55	0.0769	ns	0.4614	ns	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.300	ns	0.9	ns	NA	NA	NA	NA
control	low	high	51	55	0.711	ns	0.9	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.314	ns	0.9	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_attitude
##             Sum Sq  Df F value  Pr(>F)  
## ai_training  15.49   2  2.7132 0.06781 .
## Residuals   936.15 328                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.02 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.13 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_attitude
##           Sum Sq  Df F value Pr(>F)
## stakes      5.42   1  1.8837 0.1709
## Residuals 946.22 329               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 5.69e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.08 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.9370	ns	0.9370	ns	-0.0104	115	104	-0.290	0.27	negligible
yes_ai	no_ai	116	113	0.0464		0.1305	ns	0.2600	115	112	0.005	0.54	small
control	no_ai	106	113	0.0435		0.1305	ns	0.2883	104	112	0.010	0.57	small

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.171	ns	0.171	ns	0.1509	164	167	-0.06	0.37	negligible

Regression (exploratory)

Ai Feeling

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	ai_feeling	57	3.596	1.602	0.212	0.425
high	yes_ai	ai_feeling	58	3.069	1.927	0.253	0.507
low	control	ai_feeling	48	3.312	1.715	0.248	0.498
high	control	ai_feeling	54	3.093	1.557	0.212	0.425
low	no_ai	ai_feeling	57	2.930	1.710	0.226	0.454
high	no_ai	ai_feeling	55	2.618	1.533	0.207	0.415

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	ai_feeling	115	3.330	1.786	0.167	0.330
control	ai_feeling	102	3.196	1.629	0.161	0.320
no_ai	ai_feeling	112	2.777	1.626	0.154	0.304

By stakes

stakes	variable	n	mean	sd	se	ci
low	ai_feeling	162	3.278	1.688	0.133	0.262
high	ai_feeling	167	2.928	1.692	0.131	0.258

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_feeling
##                    Sum Sq  Df F value  Pr(>F)  
## ai_training         19.27   2  3.4092 0.03426 *
## stakes              10.58   1  3.7418 0.05394 .
## ai_training:stakes   1.37   2  0.2425 0.78481  
## Residuals          912.99 323                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.02 | [0.00, 1.00]
## stakes             |           0.01 | [0.00, 1.00]
## ai_training:stakes |       1.50e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                0.15 | [0.03, Inf]
## stakes             |                0.11 | [0.00, Inf]
## ai_training:stakes |                0.04 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0.3880	ns	0.7760	ns	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0.0351		0.2106	ns	NA	NA	NA	NA
low	control	no_ai	51	58	0.2450	ns	0.7350	ns	NA	NA	NA	NA
high	yes_ai	control	58	55	0.9410	ns	0.9410	ns	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0.1580	ns	0.7200	ns	0.2581	-0.13	0.65	small
high	control	no_ai	55	55	0.1440	ns	0.7200	ns	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.114	ns	0.342	ns	NA	NA	NA	NA
control	low	high	51	55	0.499	ns	0.626	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.313	ns	0.626	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_feeling
##             Sum Sq  Df F value  Pr(>F)  
## ai_training  18.75   2   3.304 0.03797 *
## Residuals   924.94 326                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.02 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      0.14 | [0.02, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_feeling
##           Sum Sq  Df F value Pr(>F)  
## stakes     10.05   1  3.5207 0.0615 .
## Residuals 933.64 327                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter | Eta2 |       95% CI
## -------------------------------
## stakes    | 0.01 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.10 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0.5580	ns	0.5580	ns	0.0784	115	102	-0.18	0.36	negligible
yes_ai	no_ai	116	113	0.0138		0.0414	*	0.3240	115	112	0.06	0.59	small
control	no_ai	106	113	0.0699	ns	0.1398	ns	0.2576	102	112	0.02	0.57	small

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.0615	ns	0.0615	ns	0.2069	162	167	0.0031	0.43	small

Regression (exploratory)

Ai Use (single item)

Ai Use

Summary

Both factors

stakes	ai_training	variable	n	mean	sd	se	ci
low	yes_ai	ai_use	55	4.636	1.253	0.169	0.339
high	yes_ai	ai_use	58	4.983	0.868	0.114	0.228
low	control	ai_use	50	3.180	0.983	0.139	0.279
high	control	ai_use	54	3.093	0.937	0.128	0.256
low	no_ai	ai_use	57	1.439	1.488	0.197	0.395
high	no_ai	ai_use	55	1.836	1.630	0.220	0.441

By ai_training

ai_training	variable	n	mean	sd	se	ci
yes_ai	ai_use	113	4.814	1.082	0.102	0.202
control	ai_use	104	3.135	0.956	0.094	0.186
no_ai	ai_use	112	1.634	1.565	0.148	0.293

By stakes

stakes	variable	n	mean	sd	se	ci
low	ai_use	162	3.062	1.837	0.144	0.285
high	ai_use	167	3.335	1.765	0.137	0.270

Two-Way ANOVA

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_use
##                    Sum Sq  Df  F value  Pr(>F)    
## ai_training        567.63   2 187.3961 < 2e-16 ***
## stakes               4.23   1   2.7925 0.09567 .  
## ai_training:stakes   3.79   2   1.2496 0.28801    
## Residuals          489.19 323                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Eta2 (partial) |       95% CI
## --------------------------------------------------
## ai_training        |           0.54 | [0.48, 1.00]
## stakes             |       8.57e-03 | [0.00, 1.00]
## ai_training:stakes |       7.68e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA (Type II)
## 
## Parameter          | Cohen's f (partial) |      95% CI
## ------------------------------------------------------
## ai_training        |                1.08 | [0.96, Inf]
## stakes             |                0.09 | [0.00, Inf]
## ai_training:stakes |                0.09 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots Two-Way

stakes	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
low	yes_ai	control	58	51	0	****	0	****	NA	NA	NA	NA
low	yes_ai	no_ai	58	58	0	****	0	****	NA	NA	NA	NA
low	control	no_ai	51	58	0	****	0	****	NA	NA	NA	NA
high	yes_ai	control	58	55	0	****	0	****	NA	NA	NA	NA
high	yes_ai	no_ai	58	55	0	****	0	****	2.4273	1.88	3.28	large
high	control	no_ai	55	55	0	****	0	****	NA	NA	NA	NA

ai_training	group1	group2	n1	n2	p	p.signif	p.adj	p.adj.signif	effsize	conf.low	conf.high	Cohens’ d
yes_ai	low	high	58	58	0.089	ns	0.267	ns	NA	NA	NA	NA
control	low	high	51	55	0.644	ns	0.644	ns	NA	NA	NA	NA
no_ai	low	high	58	55	0.180	ns	0.360	ns	NA	NA	NA	NA

One-Way ANOVAs

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_use
##             Sum Sq  Df F value    Pr(>F)    
## ai_training 569.56   2  186.72 < 2.2e-16 ***
## Residuals   497.20 326                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter   | Eta2 |       95% CI
## ---------------------------------
## ai_training | 0.53 | [0.48, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter   | Cohen's f |      95% CI
## -------------------------------------
## ai_training |      1.07 | [0.95, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

## $output1
## Anova Table (Type II tests)
## 
## Response: ai_use
##            Sum Sq  Df F value Pr(>F)
## stakes       6.16   1  1.8979 0.1693
## Residuals 1060.60 327               
## 
## $output2
## # Effect Size for ANOVA
## 
## Parameter |     Eta2 |       95% CI
## -----------------------------------
## stakes    | 5.77e-03 | [0.00, 1.00]
## 
## - One-sided CIs: upper bound fixed at [1.00].
## $output3
## # Effect Size for ANOVA
## 
## Parameter | Cohen's f |      95% CI
## -----------------------------------
## stakes    |      0.08 | [0.00, Inf]
## 
## - One-sided CIs: upper bound fixed at [Inf].

Plots One-Way

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
yes_ai	control	116	106	0	****	0	****	1.6410	113	104	1.28	2.08	large
yes_ai	no_ai	116	113	0	****	0	****	2.3654	113	112	1.96	2.91	large
control	no_ai	106	113	0	****	0	****	1.1473	104	112	0.85	1.54	large

group1	group2	n1.x	n2.x	p	p.signif	p.adj	p.adj.signif	effsize	n1.y	n2.y	conf.low	conf.high	Cohens’ d
low	high	167	168	0.169	ns	0.169	ns	-0.1519	162	167	-0.4	0.05	negligible

Regression (exploratory)