Actuarial Notes

Linear Mixed Models: A Practical Guide Using Statistical Software

By Brady T. West, Kathleen B. Welch and Andrzej T. Gałecki · Chapman & Hall/CRC · 2022

Study guide: Exam MAS-II

A step-by-step guide to fitting linear mixed models (LMMs) in SAS, SPSS, R, Stata and HLM, covering the most popular packages for the task in one book. It gives a chapter to the key theory underlying LMMs for clustered, longitudinal and repeated-measures data, then analyses real-world data sets from a variety of study designs — hypothesis testing, interpretation of results and model diagnostics — with each package's code and tables of estimates that allow the results to be compared across procedures. The third edition updates every example, with new tools for visualization and interpretation, and adds a chapter on power analysis for mixed-effects models.

On the syllabus

  • Exam MAS-II — objectives B1–B4; all chapters, excluding coding examples, together with the authors' Additional Notes on Shrinkage Means.

1 Introduction

2 Linear Mixed Models: An Overview

3 Two-Level Models for Clustered Data: The Rat Pup Example

4 Three-Level Models for Clustered Data: The Classroom Example

5 Models for Repeated-Measures Data: The Rat Brain Example

6 Random Coefficient Models for Longitudinal Data: The Autism Example

7 Models for Clustered Longitudinal Data: The Dental Veneer Example

8 Models for Data with Crossed Random Factors: The SAT Score Example

9 Power Analysis and Sample Size Calculations for Linear Mixed Models

Appendix A Statistical Software Resources

Appendix B Calculation of the Marginal Covariance Matrix

Appendix C Acronyms / Abbreviations

Sources