Missing Data in Clinical Studies 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.
Missing Data in Clinical Studies 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.
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Geert Molenberghs and Michael Kenward are the authors of Missing Data in Clinical Studies, published by Wiley.
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.
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.
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.
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.
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Zustand: New. Missing Data in Clinical Studies 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. Series: Statistics in Practice. Num Pages: 526 pages, Illustrations, BIC Classification: PB. Category: (P) Professional & Vocational. Dimension: 232 x 160 x 33. Weight in Grams: 864. . 2007. 1st Edition. Hardcover. . . . . Bestandsnummer des Verkäufers V9780470849811
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