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

PSC In The News

RSS Feed icon

Shapiro says Twitter-based employment index provides real-time accuracy

Xie says internet censorship in China often reflects local officials' concerns

Cheng finds marriage may not be best career option for women

Highlights

Jeff Morenoff makes Reuters' Highly Cited Researchers list for 2014

Susan Murphy named Distinguished University Professor

Sarah Burgard and former PSC trainee Jennifer Ailshire win ASA award for paper

James Jackson to be appointed to NSF's National Science Board

Next Brown Bag


PSC Brown Bags will return in the fall

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