Results

Descriptives

Descriptives
	QuadrantCondition	SessionCondition	Accuracy
N	not saturated	baseline	4800
		conclusion	4800
	saturated	baseline	4800
		conclusion	4800
Missing	not saturated	baseline	0
		conclusion	0
	saturated	baseline	0
		conclusion	0
Mean	not saturated	baseline	0.749
		conclusion	0.711
	saturated	baseline	0.715
		conclusion	0.587
Median	not saturated	baseline	1.00
		conclusion	1.00
	saturated	baseline	1.00
		conclusion	1.00
Minimum	not saturated	baseline	0
		conclusion	0
	saturated	baseline	0
		conclusion	0
Maximum	not saturated	baseline	1
		conclusion	1
	saturated	baseline	1
		conclusion	1

Plots

Accuracy

Generalized Mixed Model

Model Info
Info	Value	Comment
Model Type	Logistic	Model for binary y
Call	glm	ACCtar ~ 1 + QuadrantCondition + sessione + QuadrantCondition:sessione
Link function	Logit	Log of the odd of y=1 over y=0
Direction	P(y=1)/P(y=0)	P( ACCtar = ) / P( ACCtar = )
Distribution	Binomial	Dichotomous event distribution of y
LogLikel.	.	More is better
R-squared	.	Marginal
R-squared	.	Conditional
AIC	.	Less is better
BIC	.	Less is better
Deviance	.	Conditional
Residual DF	.
Chi-squared/DF	.	Overdispersion indicator
Converged	.
Optimizer	.

[3]

Model Results

Fixed Effect Omnibus tests
	X²	df	p
QuadrantCondition	.	.	.
sessione	.	.	.
QuadrantCondition ✻ sessione	.	.	.

Fixed Effects Parameter Estimates
				95% Confidence Interval			95% Exp(B) Confidence Interval
Names	Effect	Estimate	SE	Lower	Upper	exp(B)	Lower	Upper	z	p
(Intercept)	(Intercept)	.	.	.	.	.	.	.	.	.
QuadrantCondition1	saturated - not saturated	.	.	.	.	.	.	.	.	.
sessione1	conclusion - baseline	.	.	.	.	.	.	.	.	.
QuadrantCondition1 ✻ sessione1	saturated - not saturated ✻ conclusion - baseline	.	.	.	.	.	.	.	.	.

Random Components
Groups	Name	SD	Variance	ICC
Residuals		.	.	.

Post Hoc Tests

Post Hoc Comparisons - QuadrantCondition ✻ sessione
Comparison
QuadrantCondition	sessione		QuadrantCondition	sessione	exp(B)	SE	t	df	p	p_holm
.	.	-	.	.	.	.	.	.	.	.
.	.	-	.	.	.	.	.	.	.	.
.	.	-	.	.	.	.	.	.	.	.
.	.	-	.	.	.	.	.	.	.	.
.	.	-	.	.	.	.	.	.	.	.
.	.	-	.	.	.	.	.	.	.	.

Effects Plots

References

[1] The jamovi project (2021). jamovi. (Version 1.6) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2020). R: A Language and environment for statistical computing. (Version 4.0) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2020-08-24).

[3] Gallucci, M. (2019). GAMLj: General analyses for linear models. [jamovi module]. Retrieved from https://gamlj.github.io/.