Multilevel Modeling
Second Edition
Volume:
143
Courses:
Quantitative Research Methods in Education | Quantitative Research Methods in Education | Research Methods in Sociology | Statistics - General Interest | Statistics in Health & Nursing | Statistics in Political Science | Statistics in Sociology | Structural Equation Modeling, Hierarchical Linear Modeling, & Multilevel Modeling
Quantitative Research Methods in Education | Quantitative Research Methods in Education | Research Methods in Sociology | Statistics - General Interest | Statistics in Health & Nursing | Statistics in Political Science | Statistics in Sociology | Structural Equation Modeling, Hierarchical Linear Modeling, & Multilevel Modeling
December 2019 | 128 pages | SAGE Publications, Inc
Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by providing a rationale for multilevel models; outlines the basic approach to estimating and evaluating a two-level model; discusses the major extensions to mixed-effects models; and provides advice for where to go for instruction in more advanced techniques. Rich with examples, the Second Edition expands coverage of longitudinal methods, diagnostic procedures, models of counts (Poisson), power analysis, cross-classified models, and adds a new section added on presenting modeling results. A website for the book includes the data and the statistical code (both R and Stata) used for all of the presented analyses.
Series Editor's Introduction
About the Author
Preface
1. The Need for Multilevel Modeling
2. Planning a Multilevel Model
3. Building a Multilevel Model
4. Assessing a Multilevel Model
5. Extending the Basic Model
6. Longitudinal Models
7. Guidance
References