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Journal ArticleDOI

On the design and analysis of randomized clinical trials with multiple endpoints.

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TLDR
Simulation is used to generate critical values and sequences of nominal significance levels for the approximate likelihood ratio test, which is not normally distributed.
Abstract
This paper considers some methods for reducing the number of significance tests undertaken when analyzing and reporting results of clinical trials. Emphasis is placed on designing and analyzing clinical trials to examine a composite hypothesis concerning multiple endpoints and combining this multiple endpoint methodology with group sequential methodology. Four methods for composite hypotheses are considered: an ordinary least squares and a generalized least squares approach both due to O'Brien (1984, Biometrics 40, 1079-1087), a new modification of these, and an approximate likelihood ratio test, due to Tang, Gnecco, and Geller (1989, Biometrika 76, 577-583). These are extended for group sequential use. In particular, simulation is used to generate critical values and sequences of nominal significance levels for the approximate likelihood ratio test, which is not normally distributed. An example is given and the relative merits of the suggested approaches are discussed.

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Citations
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Journal ArticleDOI

Bayesian sequential monitoring designs for single-arm clinical trials with multiple outcomes.

TL;DR: A Bayesian approach for monitoring multiple outcomes in single-arm cancer trials, including bio-chemotherapy acute leukaemia trials, bone marrow transplantation trials, and an anti-infection trial is presented.
Journal ArticleDOI

Effects of different membranes and dialysis technologies on patient treatment tolerance and nutritional parameters

TL;DR: There was a significant decrease in pre-dialysis plasma beta 2-microglobulin levels in high-flux dialysis of 9.04 +/- 10.46 mg/liter and in hemodiafiltration of 6.35 +/- 12.28mg/liter, both using high- flux polysulfone membrane in comparison with Cuprophan and low-f Luxon membranes.
Journal ArticleDOI

Analyzing multiple endpoints in clinical trials of pain treatments: IMMPACT recommendations

TL;DR: In this paper, the authors describe the use of multiple endpoints in the design, analysis, and interpretation of pain clinical trials, and review available strategies and methods for addressing multiplicity, emphasizing the importance of specifying in advance the outcomes and clinical decision rule that will serve as the basis for determining that a treatment is efficacious and the methods that will be used to control the overall Type I error rate.
Journal ArticleDOI

Exact t and F Tests for Analyzing Studies with Multiple Endpoints

Jurgen Lauter
- 01 Sep 1996 - 
TL;DR: In this paper, the authors describe some methods of forming sum aggregates in multivariate analysis, which are useful for the statistical analysis of investigations with multiple endpoints, in particular, the sum statistics can be applied if differences between two or more populations have to be tested and a factorial structure of the means and covariances can be supposed.
References
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Book

An Introduction to Multivariate Statistical Analysis

TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
Journal ArticleDOI

Discrete sequential boundaries for clinical trials

K. K. Gordon Lan, +1 more
- 01 Dec 1983 - 
TL;DR: In this article, the authors proposed a more flexible method to construct discrete sequential boundaries based on the choice of a function, a*(t), which characterizes the rate at which the error level ac is spent.
Book

Order restricted statistical inference

TL;DR: In this paper, a set of multinomial parameters are derived about distributions subject to shape restrictions, and a conditional expectation given a sigma-lattice is given in a more general setting.
Journal ArticleDOI

Group sequential methods in the design and analysis of clinical trials

TL;DR: In this article, a group sequential design is proposed to divide patient entry into a number of equal-sized groups so that the decision to stop the trial or continue is based on repeated significance tests of the accumulated data after each group is evaluated.