American Statistical Association
New York City
Metropolitan Area Chapter

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



ESTIMATING THE CAUSAL EFFECT OF RANDOMIZATION
VERSUS TREATMENT PREFERENCE

by

Sue Marcus, Ph.D.
Assistant Professor
Department of Psychiatry
Mount Sinai School of Medicine


Abstract

Randomization is the gold standard for comparing a treatment versus a control condition but randomization is not always feasible or ethical when an individual has a strong preference for the treatment or control conditions. In addition, compliance or motivation may be better with a preferred treatment. On the other hand, nonrandomized studies often suffer from selection bias. The doubly-randomized preference trial (DRPT) is a hybrid randomized and nonrandomized design that allows for estimation of the causal effect of randomization versus treatment preference. In the DRPT, individuals are randomized to either randomization or choice of treatment versus control. We will show how the potential outcomes framework can be used to derive an unbiased estimate of the causal effect of randomization versus preference in the DRPT. The methodology will be illustrated using a DRPT of introductory psychology students who were randomized to randomized assignment or preference of mathematics versus vocabulary training. Our results indicate a significant randomization versus preference effect on mathematics outcomes for those who received mathematics training.

Biographical Note

Sue M. Marcus is Assistant Professor of Psychiatry and Mathematics in the Department of Psychiatry of the Mount Sinai School of Medicine. She received an M.S. in Biostatistics from Harvard School of Public Health and a Ph.D. in Statistics from the Wharton School of the University of Pennsylvania where she did her dissertation under the supervision of Paul Rosenbaum. Dr. Marcus has written and consulted extensively on observational study methods for bias in longitudinal mental health studies. Dr. Marcus is a Research Scientist at the Center for Health Statistics at the University of Illinois at Chicago, a leading center for the development of statistical methods for causal inference in longitudinal studies. She has been a Scientific Advisor to the NIMH multisite TADS trial and statistical consultant for the NIMH multisite Multimodal Treatment for Children with ADHD (MTA) Follow-up Study.


Date: Wednesday, February 18, 2009
Time: 2:00 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
Biostatistics Computer Lab
6th Floor - Room 656
New York, New York

RESERVATIONS ARE NOT REQUIRED

Coffee will be served.


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