Missing Data in Clinical Studies

Missing Data in Clinical Studies provides a comprehensiveaccount of the problems arising when data from clinical and relatedstudies are incomplete, and presents the reader with approaches toeffectively address them. The text provides a critique ofconventional and simple methods before moving on to discuss moreadvanced approaches. The authors focus on practical and modelingconcepts, providing an extensive set of case studies to illustratethe problems described.

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

Missing Data in Clinical Studies has been developedthrough a series of courses and lectures. Its practical approachwill appeal to applied statisticians and biomedical researchers, inparticular those in the biopharmaceutical industry, medical andpublic health organisations. Graduate students of biostatisticswill also find much of benefit.