title: Sample size recalculation using conditional power.
abstract: The sample size required to achieve a given power at a prespecified absolute difference in mean response may depend on one or more nuisance parameters, which are usually unknown. Proposed methods for using an internal pilot to recalculate the sample size using estimates of these parameters have been well studied. Most of these methods ignore the fact that data on the parameter of interest from within this internal pilot will contribute towards the value of the final test statistic. We propose a method which involves recalculating the target sample size by computing the number of further observations required to maintain the probability of rejecting the null hypothesis at the end of the study under the prespecified absolute difference in mean response conditional on the data observed so far. We do this within the framework of a two-group error-spending sequential test, modified so as to prevent inflation of the type I error rate.
authors.affiliation: Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, U.S.A. denne.jonathan@lilly.com
authors.forename: J S
authors.initials: JS
authors.lastname: Denne
mesh_terms: D001943:Breast Neoplasms / Q000188:drug therapy; D002986:Clinical Trials as Topic / Q000379:methods*; D004358:Drug Therapy; D005260:Female; D006801:Humans; D009503:Neutropenia / Q000188:drug therapy; D009716:Numerical Analysis, Computer-Assisted; D018401:Sample Size