All Times EDT
Keywords: Missing data, Imputation
How to properly handle missing data in the statistical analysis of randomized clinical trials has been a growing concern the industry for many years. This past year has proven to be especially challenging with the arrival of a pandemic. The potential bias due to missing data depends on what caused the data to be missing. The statistical methods used to analyze this data becomes very important. Various methods of imputation will be employed, including an observed case analysis with no imputation, and the results will be compared in terms of study outcome on bioequivalence and superiority to placebo.