Applied longitudinal data analysis for epidemiology : a practical guide / Jos W.R. Twisk.
Material type:
TextPublication details: Cambridge, UK ; New York : Cambridge University Press, 2003.Description: 1 online resource (xvi, 301 pages) : illustrationsContent type: - text
- computer
- online resource
- 0511070063
- 9780511070068
- 0511061609
- 9780511061608
- 0511055277
- 9780511055270
- 0511121105
- 9780511121104
- 1280162503
- 9781280162503
- 9780521819763
- 0521819768
- 9780521525800
- 0521525802
- Epidemiology -- Research -- Statistical methods
- Epidemiology -- Longitudinal studies
- Epidemiology -- Statistical methods
- Longitudinal method
- Epidemiologic Studies
- Data Interpretation, Statistical
- Longitudinal Studies
- Models, Statistical
- Épidémiologie -- Recherche -- Méthodes statistiques
- Épidémiologie -- Études longitudinales
- Épidémiologie -- Méthodes statistiques
- Méthode longitudinale
- MEDICAL -- Health Risk Assessment
- MEDICAL -- Epidemiology
- Epidemiology
- Epidemiology -- Statistical methods
- Epidemiologie
- Statistiek
- Longitudinaal onderzoek
- Epidemiologia
- Métodos epidemiológicos
- Estudos longitudinais
- 614.4/07/27 22
- RA652.2.M3 T95 2003eb
- 2003 H-678
- WA 105
- 44.11
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Includes bibliographical references (pages 286-294) and index.
Cover; Half-title; Title; Copyright; Dedication; Contents; Preface; Acknowledgements; 1 Introduction; 2 Study design; 3 Continuous outcome variables; 4 Continuous outcome variables -- relationships with other variables; 5 Other possibilities for modelling longitudinal data; 6 Dichotomous outcome variables; 7 Categorical and 'count' outcome variables; 8 Longitudinal studies with two measurements: the definition and analysis of change; 9 Analysis of experimental studies; 10 Missing data in longitudinal studies; 11 Tracking; 12 Software for longitudinal data analysis; 13 Sample size calculations.
In this book the most important techniques available for longitudinal data analysis are discussed, including simple techniques such as the paired t-test and summary statistics, and more sophisticated techniques such as generalised estimating equations and random coefficient analysis. This practical guide is suitable for non-statisticians involved in medical research and epidemiology.
Print version record.
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