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

PSC In The News

RSS Feed icon

Neidert says decreasing relevance of marriage reflected in growing percent of one-person households

House says resolving socioeconomic inequalities, not spending more on health care, will improve health in America

Kusunoki, Hall, and Barber find obese teen girls less likely to use birth control

Highlights

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

Elizabeth Bruch wins ASA award for paper in mathematical sociology

Next Brown Bag

PSC Brown Bags will be back fall 2015


Sample size formulae for two-stage randomized trials with survival outcomes

Publication Abstract

Li, Zhiguo, and Susan A. Murphy. 2011. "Sample size formulae for two-stage randomized trials with survival outcomes." Biometrika, 98(3): 503-518.

Two-stage randomized trials are growing in importance in developing adaptive treatment strategies, i.e. treatment policies or dynamic treatment regimes. Usually, the first stage involves randomization to one of the several initial treatments. The second stage of treatment begins when an early nonresponse criterion or response criterion is met. In the second-stage, nonresponding subjects are re-randomized among second-stage treatments. Sample size calculations for planning these two-stage randomized trials with failure time outcomes are challenging because the variances of common test statistics depend in a complex manner on the joint distribution of time to the early nonresponse criterion or response criterion and the primary failure time outcome. We produce simple, albeit conservative, sample size formulae by using upper bounds on the variances. The resulting formulae only require the working assumptions needed to size a standard single-stage randomized trial and, in common settings, are only mildly conservative. These sample size formulae are based on either a weighted Kaplan-Meier estimator of survival probabilities at a fixed time-point or a weighted version of the log-rank test.

DOI:10.1093/biomet/asr019 (Full Text)

PMCID: PMC3254237. (Pub Med Central)

Browse | Search : All Pubs | Next