Online Program Home
My Program

Abstract Details

Activity Number: 128 - SPEED: Biometrics and Biostatistics Part 1
Type: Contributed
Date/Time: Monday, July 29, 2019 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #306831 Presentation
Title: A Comparison of Stacked and Pooled Multiple Imputation
Author(s): Paul Bernhardt*
Companies: Villanova University
Keywords: Multiple Imputation; Missing Data; Stacked Multiple Imputation; Bootstrapping

A stacked multiple imputation approach stacks the M imputed data sets into a single data set in order to obtain parameter estimates. Due to challenges in standard error estimation with the stacked approach, a pooled multiple imputation approach is instead usually used, where estimates are obtained for each imputed data set and combined using Rubin’s rules. We explore missing data situations where a stacked approach may have potential advantages, such as small sample sizes, categorical outcomes, or when bootstrapping is of interest. We consider several different simulation scenarios and multiple methods for obtaining standard errors for the stacked data estimates.

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

Back to the full JSM 2019 program