| Autor: |
Andriamiarana, Vivato, Kilian, Pascal, Kelava, Augustin, Brandt, Holger |
| Předmět: |
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| Zdroj: |
Structural Equation Modeling; Sep/Oct2023, Vol. 30 Issue 5, p789-806, 18p |
| Abstrakt: |
Although small sample sizes represent an important issue, few studies investigated the requirements in dynamic latent variable model frameworks (e.g., dynamic structural equation modeling, DSEM; dynamic latent class analysis, DLCA). We conduct a small sample performance study of Bayesian estimation for the non-linear dynamic latent class structural equation model which generalizes DSEM and DLCA to include time-dependent latent class transitions. We simulate data using a two-level (non-linear) dynamic latent class model with a varying number of subjects ( N = 10 , 25 , 50 , 75 ) and time points (T = 10, 25, 50) which are in our main focus among other simulation conditions. The results show that at least a sample size of N ≥ 50 with T ≥ 25 is required to ensure good estimates. Using diffuse priors on the between level, especially for the (co-)variance parameters and the factor loadings should be avoided. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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