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.
* Provides a practical guide to the analysis of clinical trials
and related studies with missing data.
* Examines the problems caused by missing data, enabling a
complete understanding of how to overcome them.
* Presents conventional, simple methods to tackle these problems,
before addressing more advanced approaches, including sensitivity
analysis, and the MAR missingness mechanism.
* Illustrated throughout with real-life case studies and worked
examples from clinical trials.
* Details the use and implementation of the necessary statistical
software, primarily SAS.
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.
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