Table 3.

Summary of the Logistic Regression DIF analyses for the TEC components

						DIF classification criteria
Component	H 0 Hypotheses	$\widehat{\beta }$	Wald chi-square	p-value	Δ Nagelkerke R 2	Jodoin and Gierl (2001)	ETS
Recognition
	No non-uniform DIF	−0.434	0.619	.431	0.004	Negligible DIF	–
	No uniform DIF	0.283	0.250	.617	0.002	Negligible DIF	Negligible DIF
External cause
	No non-uniform DIF	−0.055	0.027	.869	0.000	Negligible DIF	–
	No uniform DIF	−0.100	0.081	.776	0.000	Negligible DIF	Negligible DIF
Desire
	No non-uniform DIF	0.340	2.556	.110	0.007	Negligible DIF	–
	No uniform DIF	−0.382	1.796	.180	0.005	Negligible DIF	Negligible DIF
Belief
	No non-uniform DIF	0.235	3.169	.075	0.010	Negligible DIF	–
	No uniform DIF	0.393	2.841	.092	0.009	Negligible DIF	Negligible DIF
Memory
	No non-uniform DIF	0.248	1.909	.167	0.006	Negligible DIF	–
	No uniform DIF	−0.216	0.660	.416	0.002	Negligible DIF	Negligible DIF
Regulation
	No non-uniform DIF	−0.274	1.905	.168	0.005	Negligible DIF -
	No uniform DIF	0.393	2.063	.151	0.005	Negligible DIF	Negligible DIF
Hiding
	No non-uniform DIF	−0.366	3.314	.069	0.008	Negligible DIF	–
	No uniform DIF	−0.053	0.037	.848	0.000	Negligible DIF	Negligible DIF
Mixed
	No non-uniform DIF	−0.243	1.085	.298	0.003	Negligible DIF	–
	No uniform DIF	0.094	0.103	.748	0.000	Negligible DIF	Negligible DIF
Morality
	No non-uniform DIF	−0.264	1.506	.220	0.006	Negligible DIF	–
	No uniform DIF	0.486	2.400	.121	0.009	Negligible DIF	Negligible DIF

H ₀ Hypotheses: No non-uniform DIF (H _o: β ₃ = 0 (Model 3)). No uniform DIF (H _o: β ₂ = 0 (Model 2))

$\widehat{\beta }:\widehat{\beta }$ coefficient calculated in the LR model 3 (${\widehat{\beta }}_{\mathrm{3}}$) and LR model 2 (${\widehat{\beta }}_{\mathrm{2}}$). ${\widehat{\beta }}_{\mathrm{2}}$> 0 indicate DIF in favour of the reference group (girls), and ${\widehat{\beta }}_2$< 0 indicate DIF in favour of the focal group (boys)

Wald chi-square: Wald statistic used to test the corresponding null hypotheses. That statistic follows a chi-squared distribution with one degree of freedom

Δ Nagelkerke R ²: Measure of the magnitude of DIF based on Nagelkerke’s R ²

DIF classification criteria: Classification of DIF based on the criteria proposed by Jodoin and Gierl (2001) and the Educational Testing Service (ETS): negligible DIF/ moderate DIF/ large DIF

This results have been obtained using the purified total test score (second stage). The total test score for each examinee was refined by removing the component belief that was found to show DIF in the first stage (−2 log likelihood [model 3-model 1] = 6.125171, df = 2, p = .047)