Table 3.

Fit Statistics for the One-Factor, Oblique Two-Factor, Orthogonal Method Effects Two-Factor–with Positive Specific Factor, and Orthogonal Method Effects Two-Factor with Negative Specific Factor Configural Invariance Models of the LOT-R

Model	S-Bχ2	df	p	CFIa	SRMRb	RMSEAb
One-Factor
English	42.47	9	<.01	0.72	0.09	0.14
Spanish	28.71	9	<.01	0.79	0.07	0.10
Oblique Two-Factor
English	15.71	8	0.047	0.94	0.05	0.07
Spanish	13.95	8	0.083	0.94	0.04	0.06
Orthogonal Method Effects Two-Factor – Positive Specific Factor
English	4.69	6	0.585	1.00	0.02	0.00
Spanish	12.00	6	0.062	0.94	0.04	0.07
Orthogonal Method Effects Two-Factor – Negative Specific Factor
English	12.00	6	0.062	0.95	0.04	0.07
Spanish	11.18	6	0.083	0.95	0.03	0.06

Note. S-B = Satorra-Bentler; CFI = robust comparative fit index; SRMR = standardized root mean square residual; RMSEA = root mean square error of approximation.

^aAcceptable fit > .90, Good fit >.95.

^bAcceptable fit < .08, Good fit < .05.