American Statistical Association
New York City
Metropolitan Area Chapter

New York State Psychiatric Institute
at Columbia University Medical Center
Biostatistics Seminar



WEIGHTING ESTIMATORS FOR COX REGRESSION WITH MISSING COVARIATES

by

Myunghee Cho Paik, Ph.D.
Department of Biostatistics
Columbia University


Abstract

When new covariates are collected in the middle of a follow-up study, these covariates may not be available for those who already died or dropped out of the study. In this talk, we propose a method handling this situation in the Cox proportional hazard model for survival data. We consider a weighting method and the associated augmented reweighting method for Cox model with missing covariates. The proposed method provides consistent and asymptotically normally distributed estimators when the missing-data mechanism depends on the outcome variables as well as on the observed covariates with either monotone or arbitrary non-monotone missingness patterns. Simulation results indicate that, in common situations, the proposed reweighting estimators are equally or more efficient than the inverse probability weighting estimators. The simple reweighting estimators can be easily implemented in standard statistical packages such as SAS or SPLUS. We illustrate the method using Northern Manhattan Stroke Study.

Biographical Note

Dr. Myunghee Cho Paik is a Professor of Biostatistics in the Department of Biostatistics at Columbia University. She has approximately 100 publications in such areas as missing data, survival analysis, GEE and longitudinal data analysis. She is the co-author of a widely used textbook entitled Statistical Methods for Rates and Proportions.


Date: Tuesday, April 7, 2009
Time: 3:00 - 4:00 P.M.
Location: New York State Psychiatric Institute
1051 Riverside Drive
6th Floor Multipurpose Room (6602)
New York, New York
(Directions)

RESERVATIONS ARE NOT REQUIRED

Coffee: 2:45 to 3:00 P.M.
Reception: 4:00 to 4:30 P.M.


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