Results 201 to 210 of about 353,062 (253)

A Unifying Family of Group Sequential Test Designs

Biometrics, 1999
Summary. Currently, the design of group sequential clinical trials requires choosing among several distinct design categories, design scales, and strategies for determining stopping rules. This approach can limit the design selection process so that clinical issues are not fully addressed. This paper describes a family of designs that unifies previous
John M Kittelson
exaly   +4 more sources

A Practical Comparison of Group-Sequential and Adaptive Designs

Journal of Biopharmaceutical Statistics, 2005
Sequential methods provide a formal framework by which clinical trial data can be monitored as they accumulate. The results from interim analyses can be used either to modify the design of the remainder of the trial or to stop the trial as soon as sufficient evidence of either the presence or absence of a treatment effect is available.
Nigel Stallard, Patrick Kelly, Susan Todd   +2 more
exaly   +3 more sources

Sequential methods and group sequential designs for comparative clinical trials

Fundamental and Clinical Pharmacology, 2003
AbstractComparative clinical trials are performed to assess whether a new treatment has superior efficacy than a placebo or a standard treatment (one‐sided formulation) or whether two active treatments have different efficacies (two‐sided formulation) in a given population.
Eric BELLISSANT, Véronique Sébille
exaly   +3 more sources

Adaptive Group Sequential Designs for Clinical Trials: Combining the Advantages of Adaptive and of Classical Group Sequential Approaches

Biometrics, 2001
A general method is presented integrating the concept of adaptive interim analyses into classical group sequential testing. This allows the researcher to represent every group sequential plan as an adaptive trial design and to make design changes during the course of the trial after every interim analysis in the same way as with adaptive designs.
H H Müller, Helmut Schafer
exaly   +3 more sources

Designs for group sequential tests

Controlled Clinical Trials, 1984
Several authors have proposed group sequential procedures to satisfy the ethical need in clinical trials for interim analyses. We propose here an alternative procedure that offers a good opportunity for early termination when initial results are extreme, while essentially maintaining the power provided by the procedure that applies when the ...
T R, Fleming, D P, Harrington, P C, O'Brien   +2 more
openaire   +2 more sources

Probability of success and group sequential designs

Pharmaceutical Statistics, 2023
AbstractIn this article, I extend the use of probability of success calculations, previously developed for fixed sample size studies to group sequential designs (GSDs) both for studies planned to be analyzed by standard frequentist techniques or Bayesian approaches.
openaire   +2 more sources

Group Sequential Designs for Clinical Trials

Biometrics, 1973
Group sequential procedures which are truly closed are developed for situations in which the probability of success for Treatment 1 is pi, that for Treatment 2 is P2, and the experimental objective is to test the hypothesis that pi = P2. The experiment then consists of a specified maximum number of groups or stages each containing an equal number of ...
G L, Elfring, J R, Schultz
openaire   +2 more sources

Symmetric Group Sequential Test Designs

Biometrics, 1989
In Phase III clinical trials, ethical considerations often demand interim analyses in order that the better treatment be made available to all patients as soon as possible. Group sequential test designs that do not treat the hypotheses symmetrically may not fully address this concern since early termination of the study may be easier under one of the ...
S S, Emerson, T R, Fleming
openaire   +2 more sources

Group Sequential Designs for Monitoring Survival Probabilities

Biometrics, 1996
In the present paper we derive the asymptotic joint distribution of the Nelson-Aalen estimators for the cumulative hazard function (or the Kaplan-Meier estimators for the survival function) calculated at different (possibly random) calendar time points of a survival study.
Lin, D. Y., Shen, L., Ying, Z., Breslow, N. E.   +3 more
openaire   +2 more sources