Description

Book Synopsis

Multilevel and Longitudinal Modeling Using Stata, Fourth Edition, is a complete resource for learning to model data in which observations are grouped. With 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.



Table of Contents

I. Preliminaries 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

Multilevel and Longitudinal Modeling Using Stata,

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    A Paperback / softback by Sophia Rabe-Hesketh, Anders Skrondal

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      Book details

      Publisher Stata Press
      Published 22 October 2021
      ISBN-13 9781597181372
      978-1597181372
      ISBN-10 1597181374
      Also in:
      Mathematics Probability and statistics Psychological methodology

      Description

      Book Synopsis

      Multilevel and Longitudinal Modeling Using Stata, Fourth Edition, is a complete resource for learning to model data in which observations are grouped. With 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.



      Table of Contents

      I. Preliminaries 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

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