American Statistical Association
New York City
Metropolitan Area Chapter

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



THE USE OF PROPENSITY SCORES TO ASSESS GENERALIZABILITY

by

Elizabeth Stuart, Ph.D.
Assistant Professor
Department of Mental Health and Department of Biostatistics
Johns Hopkins Bloomberg School of Public Health


Abstract

Randomized trials remain the most accepted design for estimating the effects of interventions but they do not necessarily answer a question of primary interest: Will the program be effective in a target population in which it may be implemented? In other words, are the results generalizable? There has been very little statistical research on how to assess the external validity of randomized trials. This work proposes the use of propensity-score-based metrics to quantify the similarity of the participants in a randomized trial and a population of interest, taking advantage of increased availability of population-level data. In this setting, the propensity score model models membership in the trial of interest, given a set of covariates. The resulting propensity scores are used first to quantify the difference between the trial participants and the broader population, and then to weight the control group outcomes to the population, assessing how well the weighted outcomes track the outcomes actually observed in the population. These metrics can serve as a first step in assessing the generalizability of results from randomized trials to broader populations of interest. This talk will present these ideas, discuss the assumptions underlying the approach, and illustrate the metrics using data on the evaluation of a school wide behavior improvement program.

Biographical Note

Elizabeth A. Stuart received her Ph.D. in Statistics in 2004 and is now an Assistant Professor in the Department of Mental Health and the Department of Biostatistics at Johns Hopkins Bloomberg School of Public Health. Her research interests involve methodological developments for prevention and intervention research, particularly regarding causal inference and missing data techniques. Her primary research interests are in the use of matching methods for causal inference, including the use of multiple control groups, diagnostics of matching methods, and sensitivity analyses. Application areas she has been involved in include evaluating school-wide interventions, examining the effects of adolescent drug use on adult outcomes, and the use of historical patient data to supplement a clinical trial. She recently received a K25 award from the National Institute of Mental Health, to investigate methods for generalizing results from randomized trials to target populations, with a focus on preventive interventions in mental health.


Date: Tuesday, October 20, 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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