Preventing and Treating Missing Data in Longitudinal Clinical Trials: A Practical Guide (Practical Guides to Biostatistics and Epidemiology)

Craig H. Mallinckrodt

ISBN 10: 110767915X / ISBN 13: 9781107679153

Published by Cambridge University Press, 2013

About this Item

Focuses on the prevention and treatment of missing data in longitudinal clinical trials, looking at key principles and explaining analytic methods. Series: Practical Guides to Biostatistics and Epidemiology. Num Pages: 180 pages, 6 b/w illus. 32 tables. BIC Classification: MBGR1; MBNS. Category: (P) Professional & Vocational. Dimension: 247 x 175 x 11. Weight in Grams: 366. A Practical Guide. Series: Practical Guides to Biostatistics and Epidemiology. 180 pages, 6 b/w illus. 32 tables. Focuses on the prevention and treatment of missing data in longitudinal clinical trials, looking at key principles and explaining analytic methods. Cateogry: (P) Professional & Vocational. BIC Classification: MBGR1; MBNS. Dimension: 247 x 175 x 11. Weight: 360. . 2013. Illustrated. paperback. . . . .

Seller Inventory # V9781107679153

Bibliographic Details

• Title: Preventing and Treating Missing Data in Longitudinal Clinical Trials: A Practical Guide (Practical Guides to Biostatistics and Epidemiology)
• Publisher: Cambridge University Press
• Publication Date: 2013
• Language: English
• ISBN 10: 110767915X
• ISBN 13: 9781107679153
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Recent decades have brought advances in statistical theory for missing data, which, combined with advances in computing ability, have allowed implementation of a wide array of analyses. In fact, so many methods are available that it can be difficult to ascertain when to use which method. This book focuses on the prevention and treatment of missing data in longitudinal clinical trials. Based on his extensive experience with missing data, the author offers advice on choosing analysis methods and on ways to prevent missing data through appropriate trial design and conduct. He offers a practical guide to key principles and explains analytic methods for the non-statistician using limited statistical notation and jargon. The book's goal is to present a comprehensive strategy for preventing and treating missing data, and to make available the programs used to conduct the analyses of the example dataset.

About the Author

Craig H. Mallinckrodt is Research Fellow in the Decision Sciences and Strategy Group at Eli Lilly and Company. Dr Mallinckrodt has supported drug development in all four clinical phases and in several therapeutic areas. He currently leads Lilly's Advanced Analytics hub for missing data and their Placebo Response Task Force, and is a member of a number of other scientific work groups. He has authored more than 170 papers, book chapters and texts, including extensive works on missing data and longitudinal data analysis in journals such as Statistics in Medicine, Pharmaceutical Statistics, the Journal of Biopharmaceutical Statistics, the Journal of Psychiatric Research, the Archives of General Psychiatry, and Nature. He currently chairs the Drug Information Association's Scientific Working Group on Missing Data.