Missing Data in Longitudinal Studies : Strategies for Bayesian Modeling and Sensitivity Analysis


Michael J. Daniels
Bok Engelsk 2008 · Electronic books.
Annen tittel
Utgitt
Hoboken : : Taylor & Francis, , 2008.
Omfang
1 online resource (324 p.)
Opplysninger
Description based upon print version of record.. - Cover; Title; Copyright; Contents; Preface; CHAPTER 1: Description of Motivating Examples; CHAPTER 2: Regression Models for Longitudinal Data; CHAPTER 3: Methods of Bayesian Inference; CHAPTER 4: Worked Examples using Complete Data; CHAPTER 5: Missing Data Mechanisms and Longitudinal Data; CHAPTER 6: Inference about Full-Data Parameters under Ignorability; CHAPTER 7: Case Studies: Ignorable Missingness; CHAPTER 8: Models for Handling Nonignorable Missingness; CHAPTER 9: Informative Priors and Sensitivity Analysis; CHAPTER 10: Case Studies: Nonignorable Missingness; Distributions; Bibliography. - Author IndexIndex. - Focuses on how to handle missing data in longitudinal studies, offering coverage of models for longitudinal data, missing data mechanisms, and various approaches to sensitivity analysis. This book presents an overview of methods for dealing with missing data, with particular emphasis on handling dropout and causal inference.
Emner
Bayesian statistical decision theory
Longitudinal method
Sensitivity theory (Mathematics)
Analytical, Diagnostic and Therapeutic Techniques and Equipment
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Sjanger
Dewey
ISBN
9781584886099

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