Applauded for its clarity, this accessible introduction helps readers apply multilevel techniques to their research. The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software.

chapter 1|7 pages

Introduction to Multilevel Analysis

chapter 2|19 pages

The Basic Two-Level Regression Model

chapter 5|32 pages

Analyzing Longitudinal Data

chapter 8|13 pages

Multilevel Survival Analysis

chapter 9|12 pages

Cross-Classified Multilevel Models

chapter 10|16 pages

Multivariate Multilevel Regression Models

chapter 11|23 pages

The Multilevel Approach to Meta-Analysis

chapter 13|34 pages

Assumptions and Robust Estimation Methods

chapter 14|15 pages

Multilevel Factor Models

chapter 15|10 pages

Multilevel Path Models

chapter 16|11 pages

Latent Curve Models