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. 2020 Apr 2;15(4):e0230609. doi: 10.1371/journal.pone.0230609

Table 2. CFA model fit for the VEMI in three samples.

df χ2 CFI RMSEA
Undergraduate sample 1 87 359.97 .975 .056
MTurk sample 2 87 462.52 .975 .065
LISS sample 3 87 3813.69 .948 .086
Invariance tests across three samples
Configural 261 4636.19 .955 .080
Constrain factor loadings 285 4804.38 .954 .078
Constrain intercepts 309 5978.15 .942 .084
Constrain latent means 315 6306.12 .939 .086
Invariance tests across males and females in three samples (N = 7,753)
Configural 174 3884.0 .962 .074
Constrain factor loadings 186 3906.7 .962 .072
Constrain intercepts 198 3969.1 .961 .070
Constrain latent means 201 4166.3 .959 .071
Invariance tests across white and non-white participants in samples 1 and 2 (N = 2,010)
Configural 174 767.38 .977 .058
Constrain factor loadings 186 784.62 .977 .057
Constrain intercepts 198 813.65 .976 .056
Constrain latent means 201 822.39 .976 .055

df = degrees of freedom. CFI = Confirmatory Fit Index. RMSEA = Root Mean Square Error of Approximation. We used model comparison tests based on fit indices to examine measurement invariance. We established measurement invariance (all ΔCFI < .01 or all ΔRMSEA < .01; cf. Cheung & Rensvold, 2002). That is, we were able to constrain configuration, factor loadings, intercepts, and latent means across groups without a significant decrease in model fit.