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Applied Mixed Model Analysis: A Practical Guide

Applied Mixed Model Analysis: A Practical Guide

Autorzy
Wydawnictwo Cambridge University Press
Data wydania 18/04/2019
Wydanie Drugie
Liczba stron 246
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla profesjonalistów, specjalistów i badaczy naukowych
ISBN 9781108480574
Kategorie Metody badań: zagadnienia ogólne, Epidemiologia i statystyka medyczna, Prawdopodobieństwo i statystyka
Zastępuje 9780521849753
Zastąpiona przez 9781108480574
518.92 PLN (z VAT)
$140.11 / €116.24 / £104.99 /
Produkt na zamówienie
Dostawa 3-4 tygodnie
Ilość
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Opis książki

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.

Applied Mixed Model Analysis: A Practical Guide

Spis treści

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.

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