Table 3.

Chi square difference values, p-, and l-values for the scalar model where the model number refers to the item number of which the thresholds between the two time points is estimated unconstrained (all factor loadings and other thresholds are constrained).

Sample 1			Sample 2			I
Model	χ2	p	Model	χ2	p
M1	77.719	<0.0001*	M16	106.308	<0.0001*	0.00085
M2	17.674	<0.0001*	M12	29.885	<0.0001*	0.00171
M17	54.284	<0.0001*	M15	18.237	<0.0001*	0.00256
M6	48.995	<0.0001*	M6	9.874	0.001*	0.00342
M16	45.051	<0.0001*	M14	9.741	0.001*	0.00427
M11	15.203	0.001*	M4	9.139	0.002*	0.00513
M7	9.590	0.002*	M7	7.512	0.006**	0.00598
M4	7.017	0.008**	M8	6.412	0.011**	0.00684
M14	6.755	0.009**	M9	5.176	0.022**	0.00769
M13	6.493	0.011**	M5	4.235	0.039**	0.00855
M8	5.450	0.020**	M3	3.935	0.047**	0.00940
M5	3.146	0.076***	M13	3.363	0.066***	0.01026
M12	2.296	0.130***	M2	2.789	0.094***	0.01111
M3	1.477	0.224***	M17	1.156	0.282***	0.01197
M10	1.128	0.288***	M10	0.580	0.446***	0.01282
M9	1.088	0.297***	M11	0.485	0.486***	0.01368
M15	0.005	0.942***	M1	0.005	0.941***	0.01453

^*significant when p ≤ l.

^**significant when p ≤ 0.05.

^***never significant.

l = {0.05/[17^*(1+1/2+1/3+1/4+1/5+1/6+1/7+1/8+1/9+1/10+1/11+1/12+1/13+1/14+1/15+1/16+1/17)]^*c where c = 1,…,17 to obtain a new alpha value for each new test.