小编Xia*_*hao的帖子

我正在运行一个路径分析模型，但似乎模型拟合指数是完美的：CFI = 1.00，RMSEA = 0.00。然而，完美的模型拟合通常表明模型饱和。但似乎我的模型并非如此，因为我有额外的自由度。那么，如何解释CFI和RMSEA呢？非常感谢你的帮助！

lavaan (0.5-21) converged normally after  39 iterations

  Number of observations                           109

  Number of missing patterns                         6

  Estimator                                         ML
  Minimum Function Test Statistic                6.199
  Degrees of freedom                                11
  P-value (Chi-square)                           0.860

Model test baseline model:

  Minimum Function Test Statistic              150.084
  Degrees of freedom                                20
  P-value                                        0.000

User model versus baseline model:

  Comparative Fit Index (CFI)                    1.000
  Tucker-Lewis Index (TLI)                       1.067

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)              -1000.419
  Loglikelihood unrestricted model …

我正在使用 Lavaan 运行非递归模型。然而，发生了两件事我不太明白。首先，拟合优度指数和一些标准误差为“NA”。第二，不同方向的两个变量之间的两个系数不一致（非递归部分：ResidentialMobility--作者）：一个为正，另一个为负（至少应该是同一个方向；否则如何解释？）。有人可以帮我吗？如果您希望我进一步澄清，请告诉我。谢谢！

model01<-'ResidentialMobility~a*Coun
SavingMotherPercentage~e*Affect
SavingMotherPercentage~f*Author
SavingMotherPercentage~g*Recipro

Affect~b*ResidentialMobility
Author~c*ResidentialMobility
Recipro~d*ResidentialMobility

ResidentialMobility~h*Affect
ResidentialMobility~i*Author
ResidentialMobility~j*Recipro

Affect~~Author+Recipro+ResidentialMobility
Author~~Recipro+ResidentialMobility
Recipro~~ResidentialMobility


Coun~SavingMotherPercentage

ab:=a*b
ac:=a*c
ad:=a*d

be:=b*e
cf:=c*f
dg:=d*g
'

fit <- cfa(model01, estimator = "MLR", data = data01, missing = "FIML")
summary(fit, standardized = TRUE, fit.measures = TRUE)

输出：

lavaan (0.5-21) 在 93 次迭代后正常收敛

                                                  Used       Total
  Number of observations                           502         506

  Number of missing patterns                         4

  Estimator                                         ML      Robust
  Minimum Function Test Statistic                   NA          NA
  Degrees of freedom                                -2          -2
  Minimum Function Value               0.0005232772506
  Scaling …