Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Kimball's failed replication of Reinhart-Rogoff finding cited in argument for tempered public response to social science research results

Edin and Shaefer's book on destitute families in America reviewed in NYT

Johnston says rate of daily marijuana use among college students now greater than rate of daily cigarette smoking

Highlights

Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Next Brown Bag

Monday, Oct 12
Joe Grengs, Policy & Planning for Social Equity in Transportation

Inference for non-regular parameters in optimal dynamic treatment regimes

Publication Abstract

Chakraborty, B., Susan A. Murphy, and V. Strecher. 2010. "Inference for non-regular parameters in optimal dynamic treatment regimes." Statistical Methods in Medical Research, 19(3): 317-343.

A dynamic treatment regime is a set of decision rules, one per stage, each taking a patient's treatment and covariate history as input, and outputting a recommended treatment. In the estimation of the optimal dynamic treatment regime from longitudinal data, the treatment effect parameters at any stage prior to the last can be non-regular under certain distributions of the data. This results in biased estimates and invalid confidence intervals for the treatment effect parameters. In this article, we discuss both the problem of non-regularity, and available estimation methods. We provide an extensive simulation study to compare the estimators in terms of their ability to lead to valid confidence intervals under a variety of non-regular scenarios. Analysis of a data set from a smoking cessation trial is provided as an illustration.

DOI:10.1177/0962280209103013 (Full Text)

PMCID: PMC2891316. (Pub Med Central)

Browse | Search : All Pubs | Next