Author: Craig H. Mallinckrodt
Edition: 1
Publisher: Cambridge University Press
Binding: Paperback
ISBN: 110767915X
Preventing and Treating Missing Data in Longitudinal Clinical Trials: A Practical Guide (Practical Guides to Biostatistics and Epidemiology)
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. Medical books Preventing and Treating Missing Data in Longitudinal Clinical Trials. 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 Medical books Preventing and Treating Missing Data in Longitudinal Clinical Trials. Preventing and Treating Missing Data in Longitudinal Clinical Trials
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Preventing and Treating Missing Data in Longitudinal Clinical Trials
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Cambridge Univ Pr 9781107031388 Preventing and Treating Missing Data in Longitudinal Clinical Trials By Mallinckrodt, Craig Description *Author: Mallinckrodt, Craig H. *Series Title: Practical Guides to Biostatistics and Epidemiology *Subtitle: A Practical Guide *Publication Date: 2013/01/28 *Number of Pages: 165 *Binding Type: Hardcover *Language: English *Depth: 0.25 *Width: 7.00 *Height: 10.00 SKU: UBM9781107031388 Payment We accept payment via PayPal, Mastercard, Visa, American Express, Dis
Preventing and Treating Missing Data in Longitudinal Clinical Trials: A Practical Guide by Mallinckrodt, Craig [Hardcover]
Medical Book Preventing and Treating Missing Data in Longitudinal Clinical Trials
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.
