American Statistical Association
New York City
Metropolitan Area Chapter

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



Ying Wei, Ph.D.
Assistant Professor
Department of Biostatistics
Columbia University


Regression quantiles can be substantially biased when the covariates are measured with error. In this talk, we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The proposed method corrects the measurement error induced bias by constructing unbiased joint estimation equations that simultaneously hold for all the quantile levels. A simple iterative estimation algorithm to obtain the solutions of such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure.

This is joint work with Prof. Raymond J. Carroll at Texas A&M University.

Biographical Note

Dr. Ying Wei is an Assistant Professor of Biostatistics at Columbia University. She received her Ph.D. from the University of Illinois at Urbana-Champaign in Statistics. Her research interests include longitudinal growth charts, quantile regression, semi-parametric models and robust statistics.

Date: Tuesday, October 21, 2008
Time: 3:30 - 4:30 P.M.
Location: New York State Psychiatric Institute
1051 Riverside Drive
6th Floor Multi-Purpose Room (6602)
New York, New York


Refreshments will be served from 3:00 to 3:30 P.M.,
with a reception from 4:30 to 5:00 P.M.

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