• 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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