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Journal ArticleDOI

Sample size and design considerations for phase II clinical trials with correlated observations

Daniel J. Sargent, +2 more
- 01 Jun 1997 - 
- Vol. 20, Iss: 3, pp 242-252
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TLDR
This paper proposes a simple method that adjusts a standard one- or two-stage phase II design to account for loss of information due to correlated observations, and ensures that type I and type II error rate design requirements are met even in the presence of strong correlation.
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This article is published in Controlled Clinical Trials.The article was published on 1997-06-01. It has received 10 citations till now. The article focuses on the topics: Type I and type II errors & Sample size determination.

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Citations
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Journal ArticleDOI

Generalized Estimating Equations in Longitudinal Data Analysis: A Review and Recent Developments

TL;DR: A systematic review on GEE including basic concepts as well as several recent developments due to practical challenges in real applications, including the selection of “working” correlation structure, sample size and power calculation, and the issue of informative cluster size are covered.
Journal ArticleDOI

Sample size and power calculations with correlated binary data

TL;DR: This article derives some explicit formulas for sample size and power calculations under various common situations based on using the robust variance estimator in GEE, believing that these formulas will facilitate the practice in planning two-arm clinical trials with correlated binary outcome data.
Journal ArticleDOI

An optimal two-stage phase II design utilizing complete and partial response information separately

TL;DR: It is argued that CRs and PRs should be considered separately, and hence a two-stage design with a multilevel endpoint (i.e., CR, PR, and nonresponders) is proposed and results in an improvement in expected sample size compared to Simon's optimal design.
Journal ArticleDOI

Balanced two-stage designs for phase II clinical trials:

TL;DR: The balanced design provides an additional choice for two-stage phase II trials when the investigators would like to monitor the trial near a study's halfway point, and its total sample sizes are comparable with Simon's designs.
Journal ArticleDOI

Optimal designs for two-arm, phase II clinical trial design with multiple constraints.

TL;DR: A new design is presented in which sample size determination includes a control arm and allows for the estimation of response for each treatment as well as estimation of the difference in the response rates.
References
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Book

Generalized Linear Models

TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI

Longitudinal data analysis using generalized linear models

TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Journal ArticleDOI

Optimal two-stage designs for phase II clinical trials.

TL;DR: Two-stage designs that are optimal in the sense that the expected sample size is minimized if the regimen has low activity subject to constraints upon the size of the type 1 and type 2 errors are presented.
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