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Applied Mixed Model Analysis
A Practical Guide

2nd Edition

£99.99

Part of Practical Guides to Biostatistics and Epidemiology

  • Date Published: April 2019
  • availability: In stock
  • format: Hardback
  • isbn: 9781108480574

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About the Authors
  • 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.

    • This book is designed for researchers in applied fields with modest mathematical and statistical backgrounds
    • Emphasizes interpretation of results to address scientific questions
    • Worked examples in STATA and datasets for download support hands-on learning
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    Product details

    • Edition: 2nd Edition
    • Date Published: April 2019
    • format: Hardback
    • isbn: 9781108480574
    • length: 246 pages
    • dimensions: 253 x 178 x 18 mm
    • weight: 0.6kg
    • availability: In stock
  • 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.

  • Resources for

    Applied Mixed Model Analysis

    Jos W. R. Twisk

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  • Author

    Jos W. R. Twisk, Universiteit van Amsterdam
    Jos W. R. Twisk specializes in the methodological field of longitudinal data analysis and multilevel/mixed model analysis, about which he has written three textbooks. He has also authored a textbook on applied biostatistics in Dutch. He is director of the epidemiology Master's program of the Vrije Universiteit Medical Center, Amsterdam and Head of the Expertise Center for Applied Longitudinal Data Analysis. His main activities include applied methodological research, consulting, and teaching courses on mixed model analysis, longitudinal data analysis, multilevel analysis and applied basic statistics. He has authored and coauthored more than 650 peer-reviewed international papers.

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