Abstract
In clinical trials, missing data often happens for a variety of reasons, such as dropouts, making it difficult to analyze the primary variable measured longitudinally and to interpret the results of the primary analysis. While handling missing data sometimes causes bias in the results, there have been no established statistical approaches applied to missing data in appropriate situations. In November 2001, Committee for Proprietary Medical Product of the European Medicines Agency, issued “Points to Consider (PtC) on Missing Data”, which focuses on several points that should be taken into account when handling missing data in clinical trials. In this paper, we review the contents of this PtC, which assumes that the primary analysis is based on the ITT principle, and discuss some of the approaches for handling missing data and the difficulties in interpreting these results.
