Speaker: Ruiqi Liu, Ph.D., Biostatistician, Medpace

Title: "Analysis of Data Sets with Missing Values in Clinical Trials"

Missing data is a problem we have always encountered in clinical trials. There is no universal method for handling missing data in a clinical trial, since each trial has its own set of design and measurement characteristics. The range of approaches to modeling and inference is extremely broad, and no single method or class of methods is suitable for all situations. In the past, regulators were generally accepting of using last observation carried forward imputation because it was argued to be conservative in estimating treatment differences compared to placebo. More recently regulators have recognized that study conclusions can be greatly impacted by the approach to handling missing data. This talk will provide an introduction to imputation approaches under various assumptions and provide examples to illustrate the concepts.

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