Table 13.

Mixed model results: type of student mistake and discipline for the outcome elaboration

Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) [glmerMod]
AIC	BIC	logLik	Deviance	df.resid
489.0	520.1	− 236.5	473.0	353
Scaled residuals
Min	1Q	Median	3Q	Max
− 2.2990	− 0.9849	0.6248	0.8977	1.7339
Random effects
Name	Variance	Std. Dev
(Intercept)	2.842e− 14	1.686e-07
Number of obs: 361
Fixed effects
	Estimate	Std. Error	z-value	Pr (> ǀzǀ)
(Intercept)	0.6455	0.2395	2.695	0.00703 **
Application Mistakes regarding Knowledge	-0.1160	0.3511	− 0.330	0.74112
Analytic Mistakes	1.4491	0.6133	2.363	0.01815 *
Reproduction mistakes	− 0.7504	0.2771	− 2.708	0.00677 **
Comprehension mistakes	0.2953	0.3485	0.847	0.39681
Discipline neurology	− 0.4296	0.2510	− 1.712	0.08693
Discipline orthopaedics	− 0.9959	0.3604	− 2.763	0.00573 **
–-
Signif. codes	0 ‘***’	0.001 ‘**’	0.01 ‘*’	0.05 ‘.’	0.1. ‘’	1
Correlation of fixed effects
	(Intr)	Application mistake regarding knowledge	Analytic mistake	Reproduction mistake	Comprehension mistake	Discipline neurology
Application Mistake regarding Knowledge	− 0.528
Analytic mistake	− 0.177	0.184
Reproduction mistake	− 0.720	0.420	0.183
Comprehension mistake	− 0.488	0.325	0.181	0.405
Discipline neurology	− 0.562	0.171	− 0.070	0.246	0.081
Discipline orthopaedics	− 0.337	− 0.032	− 0.242	0.164	− 0.018	0.314
Optimizer (Nelder_Mead) convergence code: 0 (OK)
Boundary (singular) fit: see help (‘isSingular’)