Results
CFA with robust ML estimation was conducted because of violation of multivariate
normality as indicated by Mardia’s Normalized coefficient = 10.37,
p < .001. Therefore, model fit was evaluated with robust test statistics:
Satorra–Bentler χ2/df = 1.76, Robust CFI = .96, Robust RMSEA = .065, 90%
CI of Robust RMSEA [.00, .121], SRMR = .043. These fit indices indicate a good
fitting model (cf. Schweizer, 2010). Factor loadings were between .34 and .77 (see
Appendix). Cronbach’s α was .83.
ResultsCFA with robust ML estimation was conducted because of violation of multivariatenormality as indicated by Mardia’s Normalized coefficient = 10.37,p < .001. Therefore, model fit was evaluated with robust test statistics:Satorra–Bentler χ2/df = 1.76, Robust CFI = .96, Robust RMSEA = .065, 90%CI of Robust RMSEA [.00, .121], SRMR = .043. These fit indices indicate a goodfitting model (cf. Schweizer, 2010). Factor loadings were between .34 and .77 (seeAppendix). Cronbach’s α was .83.
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