Geert Molenberghs, Michael G. Kenward

Missing Data in Clinical Studies

• Gebundenes Buch

Produktbeschreibung

This book takes a practical approach, featuring examples and case studies, and is the first to concentrate on analysing data from clinical trials. It features a chapter on software, with discussion of implementation of the techniques in various different statistical software packages. The authors have many years experience researching in this area, and are recognised authorities on the subject.

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The detrimental effects of incomplete data sets on the results of clinical trials are both well known and all too commonly recurrent. It is essential that the correct statistical methodology be applied in order to effectively analyse the results of trials affected by missing data.

Missing Data in Clinical Trials provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a critique of conventional and simple methods before moving on to discuss more advanced approaches. The authors focus on practical and modeling concepts, providing an extensive set of case studies to illustrate the problems described.

_ Provides a practical guide to the analysis of clinical trials and related studies with missing data.
_ Examines the problems caused by missing data, enabling a complete understanding of how to overcome them.
_ Presents conventional, simple methods to tackle these problems, before addressing more advanced approaches, including sensitivity analysis, and the MAR missingness mechanism.
_ Illustrated throughout with real-life case studies and worked examples from clinical trials.
_ Details the use and implementation of the necessary statistical software, primarily SAS.

Missing Data in Clinical Trials has been developed through a series of courses and lectures. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations. Graduate students of biostatistics will also find much of benefit.

Produktdetails

• Statistics in Practice
• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 536
• Erscheinungstermin: 1. Mai 2007
• Englisch
• Abmessung: 235mm x 157mm x 33mm
• Gewicht: 870g
• ISBN-13: 9780470849811
• ISBN-10: 0470849819
• Artikelnr.: 21633559

Autorenporträt

Geert Molenberghs and Michael Kenward are the authors of Missing Data in Clinical Studies, published by Wiley.

Inhaltsangabe

Preface. Acknowledgements. I Preliminaries. 1 Introduction. 2 Key Examples.
3 Terminology and Framework. II Classical Techniques and the Need for
Modelling. 4 A Perspective on Simple Methods. 5 Analysis of the Orthodontic
Growth Data. 6 Analysis of the Depression Trials. III Missing at Random and
Ignorability. 7 The Direct Likelihood Method. 8 The
Expectation-Maximization Algorithm. 9 Multiple Imputation. 10 Weighted
Estimating Equations. 11 Combining GEE and MI. 12 Likelihood-Based
Frequentist Inference. 13 Analysis of the Age-Related Macular Degeneration
Trial. 14 Incomplete Data and SAS. IV Missing Not at Random. 15 Selection
Models. 16 Pattern-Mixture Models. 17 Shared-Parameter Models. 18
Protective Estimation. V Sensitivity Analysis. 19 MNAR, MAR, and the Nature
of Sensitivity. 20 Sensitivity Happens. 21 Regions of Ignorance and
Uncertainty. 22 Local and Global Influence Methods. 23 The Nature of Local
Influence. 24 A Latent-Class Mixture Model for Incomplete Longitudinal
Gaussian Data. VI Case Studies. 25 The Age-Related Macular Degeneration
Trial. 26 The Vorozole Study. References. Index.