THOUGHT LEADERSHIP

Methods for addressing missing data in longitudinal studies have been written about extensively for many years, but the focus has increased more in the past decade with the publication of the EMA Guideline on Missing Data in Confirmatory Clinical Trials and the National Research Council’s treatise on The Prevention and Treatment of Missing Data in Clinical Trials both in 2010 and the release of ICH E9 (R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials in 2017.  Case studies and new methodologies addressing the handling of missing data are published on a regular basis.  Yet for all the attention this topic receives, and perhaps because of the abundance of information on this topic, clinical researchers often do not know what data imputation approach is best for their particular clinical trial.