Handling of Not-Missing-at-Random Data

• Activity Number: 242
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Madhuja Mallick*+
• Companies: Forest Research Institute, Inc.

Abstract

Missing data is an unavoidable problem in the most clinical trials. With the increased attention from regulatory agencies, nowadays statistical analysis method to address the concern for missing data within the clinical trial has been increasingly becoming a madatory part for the primary analysis and reporting. It is not always possible to identify the pattern of missing data within a clinical trial. Sensitivity analyses are often requested by regulatory agencies to assess the robustness of primary analysis method to the assumptions about the missing data mechanism. There are different methods in the literature to address different missing mechanisms. In this presentation, an analysis method based on the estimated shift parameter will be discussed to address the potential of not missing at random (NMAR) mechanism and will be compared with some other methods in this regard based on a clinical trial example.