A strength of the book is the clear and detailed explanations of how to interpret the models presented; the graphical depictions of the models are particularly helpful in this regard. The presentation is generally at an elementary level appropriate for a general audience, and most advanced material has been reserved for special sections labeled as being more advanced.

The discussions of the interpretation of latent response models and comparisons of marginal ('population averaged') with conditional ('subject-specific') models are excellent.

In summary, this is a useful text for researchers who need to learn how to model multilevel data ….

Excerpt from “Book reviews: Multilevel and Longitudinal Modeling Using Stata” by Leroux, B. 2008.
Statistics in Medicine 27: 3212–3213.

Detailed case studies with real-world datasets are accompanied by complete code to fit models, generate functions of parameters (e.g. odds ratio versus log odds ratio and associated confidence intervals), plots of predicted values and residual analysis. All too often computer manuals leave off these important aspects of an analysis, but the authors have been careful to provide a well-rounded and complete approach to model-fitting and interpretation. The examples are taken from a variety of research settings in the medical and social sciences. … A strength of the book are the exercises at the end of each of the chapters. Chapter 4 concludes with more than seven pages of exercises that feature additional analyses of the toenail data as well as separate questions involving analysis of other datasets (all available online) and one hypothetical study concerning random intercept logistic models.

Excerpt from “Reviews of Books and Teaching Materials: Multilevel and Longitudinal Modeling Using Stata” by Horton, N. J. 2006.
American Statistician 60: 293.

The description of all models is clear. The emphasis is on explaining models, demonstrating the corresponding Stata commands for an analysis of that model, and interpreting the results. Analysis of each example is carried through completely, from initial examination of the data to model diagnostics. There are ample plots and output tables to support each analysis, and very little mathematical content to interfere with the flow of the exposition. There are exercises at the end of each chapter, and they, like the examples, span a wide range of application areas ….

Excerpt from “Book reviews: Brief reports by the editor” by Loughin, T. M. 2006.
Biometrics 62: 951.

Nicholas J. Horton’s review of Multilevel and Longitudinal Modeling Using Stata, by Sophia Rabe-Hesketh and Anders Skrondal, is generally favorable.

Excerpt from “The American Statistician Highlights: Messy Data Invade the August Issue of TAS” by Westfall, P., and R. Lund. 2006.
AMSTAT News Aug. 2006, issue 350: 7.