Ø Degrees of Freedom = 1168(自由度) Ø Minimum Fit Function Chi-Square = 3066.43 (P = 0.0) (大于0.1可接受,但对样本数非常敏感,样本过大极容易被拒绝) Ø Normal Theory Weighted Least Squares Chi-Square = 4258.93 (P = 0.0)(大于0.1可接受,但对样本数非常敏感,样本过大极容易被拒绝) Ø Estimated Non-centrality Parameter (NCP) = 3090.93(没有统计检验的准则作为依据) Ø 90 Percent Confidence Interval for NCP = (2895.16 ; 3294.15) Ø Minimum Fit Function Value = http://bbs.pinggu.org/11.84 Ø Population Discrepancy Function Value (F0) = 11.93 Ø 90 Percent Confidence Interval for F0 = (11.18 ; 12.72) Ø Root Mean Square Error of Approximation (RMSEA) = 0.10(小于0.05非常好,小于0.08比较好,小于0.1尚可接受,大于0.1不可接受) Ø 90 Percent Confidence Interval for RMSEA = (0.098 ; 0.10) Ø P-Value for Test of Close Fit (RMSEA < 0.05) = 0.00 Ø Expected Cross-Validation Index (ECVI) = 17.27(常用于评鉴模式复核效度的问题,即在同一个母群体下,类似的样本之间,模式复核效度的可能性。值越小越好,并没有一个可以决定模式是否可以接受的范围值) Ø 90 Percent Confidence Interval for ECVI = (16.51 ; 18.05) Ø ECVI for Saturated Model = 9.85 Ø ECVI for Independence Model = 61.96(Expected Cross-Validation Index (ECVI) 小于 ECVI for Independence Model ,且小于 ECVI for Saturated Model ,表示假设模式可以接受) Ø Chi-Square for Independence Model with 1225 Degrees of Freedom = 15947.65 Independence AIC = 16047.65 Ø Model AIC = 4472.93 Ø Saturated AIC = 2550.00(Model AIC 小于Independence AIC,也小于Saturated AIC ,模式可接受) Ø Independence CAIC = 16275.69 Ø Model CAIC = 4960.92 Ø Saturated CAIC = 8364.87 Ø Normed Fit Index (NFI) = 0.81(大于0.9时表示良好的适配) Ø Non-Normed Fit Index (NNFI) = 0.86(大于0.9时表示良好的适配) Ø Parsimony Normed Fit Index (PNFI) = 0.77(当比较不同的模式时,0.06至0.09的差别,被视为是模式间具有实质的差异存在。不做模式比较时,可采用大于0.5为模式通过与否的标准) Ø Comparative Fit Index (CFI) = 0.87(大于0.9时表示良好的适配) Ø Incremental Fit Index (IFI) = 0.87(大于0.9时表示良好的适配) |