Small samples (N<150) are a problem for structural equation modeling (SEM), both for estimation of model parameters, as for model-based inference. This project will develop solutions to stabilize the model estimation part, and to improve the model-based inference if the sample size is small. This will
allow researchers with sample sizes to use SEM.