Online Program Home
My Program

Abstract Details

Activity Number: 611
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract #319562
Title: On the Use of the Treatment Effect in the Imputation Model for Multiple Imputation Analyses of Missing Data
Author(s): Robert Small*
Companies: Sanofi Pasteur
Keywords: Multiple Imputation ; Missing data ; Imputation Model
Abstract:

Various authors have debated the use of the treatment effect in an imputation model for Multiple Imputation. Some have followed the advice of putting as much into the imputation model as available since we may not know the relationship between observed covariates and the missing data. But the treatment effect is a unique independent variable and the objective of the original experiment. It is central to the randomization that defines the experiment and an unfailing justification for the analyses. In this paper we define a simple model with a MCR missing pattern. The ML estimates and tests are available. We compare ML approach, the MI approach and a randomization approach analytically and with simulations.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

 
 
Copyright © American Statistical Association