This easy-to-use resource provides a clear explanation of mixed modeling techniques and theories and demonstrates the use of five popular statistical software procedures (SAS, SPSS, Stata, R/S-plus, and HLM) for fitting linear mixed models (LMMs) using real-world data.
The authors fit LMMs based on both general and hierarchical model specifications, develop the model-building process step-by-step, and demonstrate the estimation, testing, and interpretation of fixed-effect parameters and covariance parameters associated with random effects.