Table 2.

Fit Statistics of the CFA and Bifactor Models in First Half of Sample

Factors	Model	χ2	df	CFI	TLI	RMSEA	WRMR
1	unitary	2672.858*	209	0.931	0.924	0.026	3.751
2	correlated	2537.522*	208	0.935	0.928	0.025	3.646
	uncorrelated	14778.662*	209	0.592	0.549	0.063	10.530
	bifactor orthogonal	790.076*	187	0.983	0.979	0.014	1.785
	bifactor oblique	535.156*	186	0.990	0.988	0.010	1.345
3	correlated	2538.428*	206	0.935	0.927	0.026	3.644
	uncorrelated	16091.871*	209	0.556	0.509	0.066	11.284
	bifactor orthogonal	796.691*	187	0.983	0.979	0.014	1.825
	bifactor oblique	520.216*	184	0.991	0.988	0.010	1.326
	second-order	2538.431*	206	0.935	0.927	0.026	3.644
4	correlated	2175.656*	203	0.945	0.937	0.024	3.285
	uncorrelated	17243.569*	209	0.523	0.473	0.069	12.116
	bifactor orthogonal	688.078*	187	0.986	0.983	0.012	1.697
	bifactor oblique	358.122*	181	0.995	0.994	0.008	1.053
	second-order	2142.621*	205	0.946	0.939	0.023	3.294
5	correlated	1715.270*	199	0.958	0.951	0.021	2.868
	uncorrelated	23397.312*	209	0.351	0.283	0.080	14.479
	bifactor orthogonal	1847.421*	187	0.954	0.943	0.023	2.996
	bifactor oblique	342.373*	177	0.995	0.994	0.007	1.024
	second-order	2018.649*	204	0.949	0.942	0.023	3.194

Note: N = 17 327. CFA, confirmatory factor analysis; χ², Chi-Square Goodness of Fit Statistic; df, degrees of freedom; CFI, Comparative Fit Index; TLI, Tucker Lewis Index; RMSEA, Root-Mean-Square Error of Approximation; WRMR, Weighted Root Mean Square Residual. Bifactor orthogonal = correlations between specific factors fixed to zero. Bifactor oblique = correlations between specific factors freely estimated.

*Statistical significance (P < .01).