我正在尝试使用lavaan估算cfa。因为我的最终目标是测试10个数据波的测量不变性，所以我将使用三个包裹（这是几个项目的平均得分），而不是十个原始项目。
但是，我现在面临的问题是，尽管可以使用10个项目来估算cfa，但它却为带有三个宗地的模型提供了奇怪的估算。确定了模型，R没有给出任何警告或错误，在这两个模型中，我都获得了所有变量和方差的估计值，据我所知，模型规范似乎没有任何其他问题（已经在其他研究中使用过）。
有人知道这个问题可能是什么吗？
下面首先是带有项目的cfa的输出，然后是带有宗地的模型的输出。
lavaan 0.6-3 ended normally after 25 iterations
Optimization method NLMINB
Number of free parameters 20
Used Total
Number of observations 38622 38623
Estimator ML
Model Fit Test Statistic 37230.201
Degrees of freedom 35
P-value (Chi-square) 0.000
Model test baseline model:
Minimum Function Test Statistic 206650.167
Degrees of freedom 45
P-value 0.000
User model versus baseline model:
Comparative Fit Index (CFI) 0.820
Tucker-Lewis Index (TLI) 0.769
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -576140.643
Loglikelihood unrestricted model (H1) -557525.543
Number of free parameters 20
Akaike (AIC) 1152321.287
Bayesian (BIC) 1152492.518
Sample-size adjusted Bayesian (BIC) 1152428.958
Root Mean Square Error of Approximation:
RMSEA 0.166
90 Percent Confidence Interval 0.164 0.167
P-value RMSEA <= 0.05 0.000
Standardized Root Mean Square Residual:
SRMR 0.075
Parameter Estimates:
Information Expected
Information saturated (h1) model Structured
Standard Errors Standard
带包裹的模型：
lavaan 0.6-3 ended normally after 16 iterations
Optimization method NLMINB
Number of free parameters 6
Used Total
Number of observations 38622 38623
Estimator ML
Model Fit Test Statistic 0.000
Degrees of freedom 0
Minimum Function Value 0.0000000000000
Model test baseline model:
Minimum Function Test Statistic 83185.522
Degrees of freedom 3
P-value 0.000
User model versus baseline model:
Comparative Fit Index (CFI) 1.000
Tucker-Lewis Index (TLI) 1.000
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -131391.625
Loglikelihood unrestricted model (H1) -131391.625
Number of free parameters 6
Akaike (AIC) 262795.249
Bayesian (BIC) 262846.619
Sample-size adjusted Bayesian (BIC) 262827.551
Root Mean Square Error of Approximation:
RMSEA 0.000
90 Percent Confidence Interval 0.000 0.000
P-value RMSEA <= 0.05 NA
Standardized Root Mean Square Residual:
SRMR 0.000
Parameter Estimates:
Information Expected
Information saturated (h1) model Structured
Standard Errors Standard
非常感谢！