JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 242
Type: Contributed
Date/Time: Monday, August 5, 2013 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #308523
Title: Simulation Study to Compare New Hybrid Model with Pattern Mixture Model Under Missing Not at Random
Author(s): Fang Liu*+ and Jingjing Chen
Companies: Merck & Co., Inc and Accenture PLC
Keywords: Missing data ; MNAR ; dropouts
Abstract:

The analysis of longitudinal data in clinical trial presents a challenge as there are often missing data points. When data missing is caused by study design, the missingness cannot be assumed as at random (MAR) but not at random (MNAR). A hybrid model was proposed to impute missing data by incorporating multiple imputation for MAR and single imputation for MNAR classified by dropout reasons. For example, Dropouts due to adverse events and lack of efficacy are classified as MAR, while dropouts due to loss to follow-up and others are classified as MNAR. Simulations will be carried out to compare the hybrid model with pattern mixture model under Missing Not at Random (MNAR).


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

Back to the full JSM 2013 program




2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.