Sequential tests with covariates with an application to censored survival data

Abstract

The problem of incorporating covariate information into sequential tests for deciding which of two treatments is superior is considered. It is assumed that the mean response depends on a number of covariates through an appropriate link function. Two large-sample sequential tests are described, and these tests are derived when the data are censored exponential survival times. Simulation results for random allocation indicate that the error probabilities for the new tests are generally no larger than those for tests derived in the absence of covariate information.

Keywords:

• censored survival time
• clinical trial
• large-sample sequential test
• linear time trend
• link function