Table 3.

Model fit of competing measurement models

Single-factor model	2-factor model A	2-factor model B	3-factor model
CALM
χ 2(20) = 70.28, P < 0.001 RMSEA = 0.068 [0.051–0.085] CFI = 0.963 SRMR = 0.047 AIC = 9697.18 BIC = 9800.66 AICweight = 0%	χ 2(19) = 67.99, P < 0.001 RMSEA = 0.068 [0.052–0.086] CFI = 0.964 SRMR = 0.043 AIC = 9696.44 BIC = 9804.24 AICweight = 0%	χ 2(19) = 41.66, P = 0.002 RMSEA = 0.047 [0.027–0.066] CFI = 0.983 SRMR = 0.032 AIC = 9668.58 BIC = 9776.37 AICweight = 72.85%	χ 2(18) = 41.74, P = 0.001 RMSEA = 0.049 [.030–.068] CFI = 0.983 SRMR = 0.032 AIC = 9670.55 BIC = 9782.66 AICweight = 27.15%
NKI-RS
χ 2(35) = 109.96, P < 0.001 RMSEA = 0.080 [0.064–0.097] CFI = 0.936 SRMR = 0.045 AIC = 7155.64 BIC = 7270.07 AICweight = 0%	χ 2(34) = 108.15, P < 0.001 RMSEA = 0.081 [0.064–0.098] CFI = 0.936 SRMR = 0.044 AIC = 7155.74 BIC = 7273.98 AICweight = 0%	χ 2(34) = 64.85, P = 0.001 RMSEA = 0.052 [0.033–0.071] CFI = 0.974 SRMR = 0.035 AIC = 7109.43 BIC = 7227.67 AICweight = 3.40%	χ 2(32) = 54.15, P = 0.009 RMSEA = 0.045 [0.024–0.065] CFI = 0.981 SRMR = 0.030 AIC = 7102.74 BIC = 7228.60 AICweight = 96.60%

Note. See Figure 3 for the configuration of different models. Abbreviations: Akaike information criterion—AIC, Bayesian Information Criterion—BIC, Akaike weight—AIC_weight.