SEM and CFA |
Model Complexity or/and number of model parameters estimated |
Analyses in which all outcome variables are continuous |
Normally distributed data, and there are no |
Linear effects existing in data |
Existing interactions between data |
Estimation method |
The lower the reliability of the scores the higher the required sample size |
Is it a latent variable models or observed variable model? |
Less precise data requires larger samples |
Missing data require larger sample sizes |
CFA in particular |
Low number of indicators for the constructs of interest per factor requires larger samples |
Lower number of indicators per factor requires larger samples |
Indicators that covary highly with multiple factors require larger samples |
If the number of factors is high a larger sample is needed |
If covariances between factors are low a larger sample is needed |