Applied mixed model analysis : a practical guide
Author(s)
Bibliographic Information
Applied mixed model analysis : a practical guide
(Practical guides to biostatistics and epidemiology)
Cambridge University Press, 2019
- : hardback
- Other Title
-
Applied multilevel analysis
Available at 2 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
"Continues, in part: Applied multilevel analysis : a practical guide (Cambridge, UK ; New York : Cambridge University Press, 2006)"--T.p. verso (CIP)
Includes bibliographical references (p.227-233) and index
Description and Table of Contents
Description
This practical book is designed for applied researchers who want to use mixed models with their data. It discusses the basic principles of mixed model analysis, including two-level and three-level structures, and covers continuous outcome variables, dichotomous outcome variables, and categorical and survival outcome variables. Emphasizing interpretation of results, the book develops the most important applications of mixed models, such as the study of group differences, longitudinal data analysis, multivariate mixed model analysis, IPD meta-analysis, and mixed model predictions. All examples are analyzed with STATA, and an extensive overview and comparison of alternative software packages is provided. All datasets used in the book are available for download, so readers can re-analyze the examples to gain a strong understanding of the methods. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other fields.
Table of Contents
- 1. Introduction
- 2. Basic principles of mixed model analysis
- 3. What is gained by using mixed model analysis?
- 4. Logistic mixed model analysis
- 5. Mixed model analysis with other outcomes
- 6. Explaining differences between groups
- 7. Multivariable modelling
- 8. Predictions based on mixed model analysis
- 9. Mixed model analysis for longitudinal data
- 10. Multivariate mixed model analysis
- 11. Sample size calculations
- 12. Some loose ends.
by "Nielsen BookData"