Individual and population health can be improved by better targeting of treatments. This personalization requires an understanding of how treatment effectiveness differs across patient subgroups. However, in RCTs the interpretation of subgroup analysis is challenging due to the risk of spurious “false positive” results arising from multiple testing, compounded by lack of power. The analysis of large observational data sets, and the application of biomics are becoming important but still pose significant analytic challenges. We will explore some advanced methods to address these issues.
Authors: Richard Grieve, Warren Stevens, Neil Hawkins, Anirban Basu
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