9781107679153 - Preventing and Treating Missing Data in Longitudinal Clinical Trials: A Practical Guide (Practical Guides to Biostatistics and Epidemiology) von Craig Mallinckrodt (6 Ergebnisse)

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Paperback. Zustand: Brand New. 1st edition. 165 pages. 9.75x6.75x0.50 inches. In Stock.

Zustand: New. 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. . . . . Books ship from the US and Ireland.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.