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Applied Longitudinal Data Analysis for Epidemiology "A Practical Guide"

68.8
65.36
This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.

Preface
Acknowledgements
1. Introduction
2. Study design
3. Continuous outcome variables
4. Continuous outcome variables relationships with other variables
5. The modelling of time
6. Other possibilities for modelling longitudinal data
7. Dichotomous outcome variables
8. Categorical and 'count' outcome variables
9. Analysis data from experimental studies
10. Missing data in longitudinal studies
11. Sample size calculations
12. Software for longitudinal data analysis
13. One step further
References
Index
ISBN
978-1-107-69992-2
EAN
9781107699922
Editor
Cambridge University Press
Stock
NO
Idioma
Inglés
Nivel
Profesional
Formato
Encuadernado
Rústica
Páginas
333
Largo
240
Ancho
170
Peso
-
Edición
Fecha de edición
03-10-2013
Año de edición
2013
Nº de ediciones
2
Colección
-
Nº de colección
-