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9781107679153

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Dr. Mallinckrodt is, as usual, a paragon of clear writing and even clearer thinking. His commonsense, practical approach further elucidates what could otherwise be intractably complex issues. This book is an invaluable resource for anyone working on longitudinal clinical trials - statistician or not. Michael Detke, MedAvante and Indiana University This is a timely introduction to handling missing data in clinical trials, by a statistician with wide practical experience. Sensibly, the author not only focuses on the handling of the missing data in the analysis but also explores ways in which the occurrence of missing data can be minimized through appropriate design and conduct. The book touches on the most recent developments from academia and the regulators and is presented at a level that is accessible and useful for statisticians and non-statisticians alike, and so should be both widely read and influential. Mike Kenward, London School of Hygiene and Tropical Medicine Designing experiments to minimize missing data and understanding the most appropriate statistical methods to implement when analyzing a data set with missing values is of critical importance. Dr. Mallinckrodt's text is approachable to any researcher challenged with issues surrounding missing data yet is technically comprehensive enough to be a valuable addition to any statistician's library. Adam Meyers, Biogen IDEC Dr. Mallinckrodt has worked tirelessly and successfully to promote statistically sound and practically relevant and feasible methodology to handle incomplete data from clinical trials. As an opinion leader, he is well respected by the biopharmaceutical industry, the regulatory authorities, and academe. Dr. Mallinckrodt tops off quality and relevance with an engaging and savory writing style. This highly recommended text is at the same time a page turner! Geert Molenberghs, Interuniversity Institute for Biostatistics and statistical Bioinformatics Craig Mallinckrodt blended his many years of research and real-world experience on missing data with recommendations in an NRC guidance document. The result is an excellent book that offers a principled and comprehensive road map of strategies to prevent and treat missing data in longitudinal clinical trials. It is a must-read for all statisticians and non-statisticians who are interested in this topic. Christy Chuang-Stein, Pfizer, Inc. Dr. Mallinckrodt has made a difficult topic accessible to a broad audience by providing clear exposition of important concepts related to missing data. The book is a valuable translation of theory into practice, including design considerations for prevention of missing data, a clear explanation of estimands, a sensible description of an analytical road map containing sensitivity analyses, real-life examples, and open access to sophisticated and readily available software tools. There are many aspects of this practical guide that will be useful to many involved in design, analysis, and interpretation of clinical trials, whether they be in industry, academia, or government. Stephen J. Ruberg, Eli Lilly & Company

Dr. Mallinckrodt is, as usual, a paragon of clear writing and even clearer thinking. His commonsense, practical approach further elucidates what could otherwise be intractably complex issues. This book is an invaluable resource for anyone working on longitudinal clinical trials - statistician or not. Michael Detke, MedAvante and Indiana University This is a timely introduction to handling missing data in clinical trials, by a statistician with wide practical experience. Sensibly, the author not only focuses on the handling of the missing data in the analysis but also explores ways in which the occurrence of missing data can be minimized through appropriate design and conduct. The book touches on the most recent developments from academia and the regulators and is presented at a level that is accessible and useful for statisticians and non-statisticians alike, and so should be both widely read and influential. Mike Kenward, London School of Hygiene and Tropical Medicine Designing experiments to minimize missing data and understanding the most appropriate statistical methods to implement when analyzing a data set with missing values is of critical importance. Dr. Mallinckrodt's text is approachable to any researcher challenged with issues surrounding missing data yet is technically comprehensive enough to be a valuable addition to any statistician's library. Adam Meyers, Biogen IDEC Dr. Mallinckrodt has worked tirelessly and successfully to promote statistically sound and practically relevant and feasible methodology to handle incomplete data from clinical trials. As an opinion leader, he is well respected by the biopharmaceutical industry, the regulatory authorities, and academe. Dr. Mallinckrodt tops off quality and relevance with an engaging and savory writing style. This highly recommended text is at the same time a page turner! Geert Molenberghs, Interuniversity Institute for Biostatistics and statistical Bioinformatics

Author Information

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.

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