The purposes of the HLM SIG are to provide a forum for the dissemination and discussion of methodological issues related to multilevel modeling. This includes research on:  

1. All types of multilevel models (e.g., multilevel regression (HLM), SEM, IRT, factor analysis, growth, mixture, and cross-classified),
2. Multilevel optimal design (e.g., cluster random designs, statistical power, sample size, effect size, and sampling weights),
3. Causal methods for observational data with multilevel models (e.g., propensity score, instrumental variable, and regression discontinuity methods),
4. Evaluation research with multilevel models (e.g., mediation, school effectiveness, and value added modeling),
5. Estimation strategies for multilevel models (e.g., Bayesian, ML, and WSL), and
6. Multilevel model assessment (e.g., model assumptions, outliers, missing values, and goodness of fit).