Applied Mixed Model Analysis - A Practical Guide

Emphasizing interpretation of results, this hands-on guide explains why, when, and how to use mixed models with your data.

List 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.

About the author

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.

Summary

This book explains all aspects of mixed model analysis without mathematical jargon, so that non-statisticians can understand the basic principles, analyze their own data, and interpret the results with confidence. Worked examples are analyzed with STATA, and all datasets are available for download, equipping readers to replicate the methods.

Product details

• Authors: Jos W R Twisk, Jos W. R. Twisk, Jos W. R. (Universiteit van Amsterdam) Twisk
• Publisher: Cambridge University Press ELT
• Languages: English
• Product format: Hardback
• Released: 28.02.2019
• EAN: 9781108480574
• ISBN: 978-1-108-48057-4
• No. of pages: 246
• Series: Practical Guides to Biostatist; Practical Guides to Biostatistics and Epidemiology; Practical Guides to Biostatist
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Media, communication > Communication science; Forschungsmethoden, allgemein, Wahrscheinlichkeitsrechnung und Statistik