z-logo
Premium
Frequentist evaluation of group sequential clinical trial designs
Author(s) -
Emerson Scott S.,
Kittelson John M.,
Gillen Daniel L.
Publication year - 2007
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2901
Subject(s) - frequentist inference , early stopping , bayesian probability , stopping rule , computer science , sequential analysis , type i and type ii errors , bayes' theorem , optimal stopping , clinical trial , econometrics , statistics , bayesian inference , mathematics , machine learning , medicine , artificial intelligence , mathematical optimization , artificial neural network , pathology
Group sequential stopping rules are often used as guidelines in the monitoring of clinical trials in order to address the ethical and efficiency issues inherent in human testing of a new treatment or preventive agent for disease. Such stopping rules have been proposed based on a variety of different criteria, both scientific (e.g. estimates of treatment effect) and statistical (e.g. frequentist type I error, Bayesian posterior probabilities, stochastic curtailment). It is easily shown, however, that a stopping rule based on one of these criteria induces a stopping rule on all other criteria. Thus, the basis used to initially define a stopping rule is relatively unimportant so long as the operating characteristics of the stopping rule are fully investigated. In this paper we describe how the frequentist operatingcharacteristics of a particular stopping rule might be evaluated to ensure that the selected clinical trial design satisfies the constraints imposed by the many different disciplines represented by the clinical trial collaborators. Copyright © 2007 John Wiley & Sons, Ltd.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom