Multilevel and Longitudinal Modeling Using Stata, Volumes I and II
- Available for pre-order. Item will ship after October 22, 2021
Multilevel and Longitudinal Modeling Using Stata, Fourth Edition, is a complete resource for learning to model data in which observations are grouped—whether those groups are formed by a nesting structure, such as children nested in classrooms, or formed by repeated observations on the same individuals. This text introduces random-effects models, fixed-effects models, mixed-effects models, marginal models, dynamic models, and growth-curve models, all of which account for the grouped nature of these types of data. As Rabe-Hesketh and Skrondal introduce each model, they explain when the model is useful, its assumptions, how to fit and evaluate the model using Stata, and how to interpret the results. With this comprehensive coverage, researchers who need to apply multilevel models will find this book to be the perfect companion. It is also the ideal text for courses in multilevel modeling because it provides examples from a variety of disciplines as well as end-of-chapter exercises that allow students to practice newly learned material.
The book comprises two volumes. Volume I focuses on linear models for continuous outcomes, while volume II focuses on generalized linear models for binary, ordinal, count, and other types of outcomes.
Table of Contents
1. Review of linear regression
II. Two-level models
3. Random-intercept models with covariates
4. Random-coefficient models
III. Models for longitudinal and panel data
Introduction to models for longitudinal and panel data (part III)
5. Subject-specific effects and dynamic models
6. Marginal models
7. Growth-curve models
IV. Models with nested and crossed random effects
8. Higher-level models with nested random effects
9. Crossed random effects
V. Models for categorical responses
10. Dichotomous or binary responses
11. Ordinal responses
12. Nominal responses and discrete choice
VI. Models for counts
VII. Models for survival or duration data
Introduction to models for survival or duration data (part VII)
14. Discrete-time survival
15. Continuous-time survival
VIII. Models with nested and crossed random effects
16. Models with nested and crossed random effects
Sophia Rabe-Hesketh is a professor of educational statistics and biostatistics at the University of California, Berkeley.
Anders Skrondal is a senior biostatistician at the Centre for Fertility and Health, Norwegian Institute of Public Health and an adjunct professor at the University of Oslo and at the University of California, Berkeley.