TABLE 2.

Fit statistics for confirmatory factor analysis models of neighborhood socio-economic status, testing levels of time-invariance

Model	Chi-square (df)	RMSEA	CFI	ΔCFI
A1: Configural invariance, 9 indicator variablesa	73,527 (294)	0.062	0.875	NA
B1: Configural invariance, 5 indicator variablesb	17,118 (72)	0.060	0.966	NA
B2: Model B1 with correlated errorc	15,122 (69)	0.058	0.970	+0.004
B3: Model B2 with weak invarianced	20,068 (77)	0.063	0.960	−0.010
B4: Model B3 with strong invariancee	86,023 (85)	0.125	0.829	−0.131
C1: Model B4 with intercepts correctedf	21,090 (85)	0.063	0.958	NA

Notes: df degrees of freedom, RMSEA root mean square error of approximation, CFI comparative fit index, ΔCFI change in comparative fit index, CFA confirmatory factor analysis

^aModel A1 is a CFA model estimated using 9 indicator variables for the socio-economic status of U.S. census tracts (i.e., household income, educational level, housing unit value, and proportions of poverty, unemployment, professional/managerial occupations, public assistance, female-headed households, and crowded housing)

^bModel B1 is a CFA model estimated using five indicator variables (i.e., household income, educational level, and proportions of poverty, unemployment, and female-headed households)

^cModel B2 adds to model B1 a correlation of the residual error terms for poverty and household income

^dModel B3 adds to model B2 the constraint that factor loadings for respective indicators are equal over time

^eModel B4 adds to model B3 the constraint that the intercepts for respective indicators are equal over time

^fModel C1 estimates model B4 using data on the five indicator variables that corrects for strong invariance