We describe a general method for finding a confidence region for a parameter vector that is compatible with the decisions of a two-stage closed test procedure in an adaptive experiment. The closed test procedure is characterized by the fact that rejection or nonrejection of a null hypothesis may depend on the decisions for other hypotheses and the compatible confidence region will, in general, have a complex, nonrectangular shape. We find the smallest cross-product of simultaneous confidence intervals containing the region and provide computational shortcuts for calculating the lower bounds on parameters corresponding to the rejected null hypotheses. We illustrate the method with an adaptive phase II/III clinical trial
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
Multinomial data occur if the major outcome of an experiment is the classification of experimental ...
We describe a general method for finding a confidence region for a parameter vector that is compatib...
We describe a general method for finding a confidence region for a parameter vector that is compatib...
We study simultaneous rank procedures for unbalanced designs with independent observations. The hypo...
The central theme of this thesis is the construction of simultaneous confidence regions (SCR) corres...
The central theme of this thesis is the construction of simultaneous confidence regions (SCR) corres...
In multiple testing, the unknown proportion of true null hypotheses among all null hypotheses that a...
To assess the effectiveness of a treatment in phase II clinical trial for cancer study, an adaptive ...
To assess the effectiveness of a treatment in phase II clinical trial for cancer study, an adaptive ...
To assess the effectiveness of a treatment in phase II clinical trial for cancer study, an adaptive ...
Multiple comparison problems arise when a set of inferences are considered simultaneously. When a se...
Many studies draw inferences about multiple endpoints but ignore the statistical implications of mul...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
Multinomial data occur if the major outcome of an experiment is the classification of experimental ...
We describe a general method for finding a confidence region for a parameter vector that is compatib...
We describe a general method for finding a confidence region for a parameter vector that is compatib...
We study simultaneous rank procedures for unbalanced designs with independent observations. The hypo...
The central theme of this thesis is the construction of simultaneous confidence regions (SCR) corres...
The central theme of this thesis is the construction of simultaneous confidence regions (SCR) corres...
In multiple testing, the unknown proportion of true null hypotheses among all null hypotheses that a...
To assess the effectiveness of a treatment in phase II clinical trial for cancer study, an adaptive ...
To assess the effectiveness of a treatment in phase II clinical trial for cancer study, an adaptive ...
To assess the effectiveness of a treatment in phase II clinical trial for cancer study, an adaptive ...
Multiple comparison problems arise when a set of inferences are considered simultaneously. When a se...
Many studies draw inferences about multiple endpoints but ignore the statistical implications of mul...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
This article considers the problem of multiple hypothesis testing using t-tests. The observed data a...
Multinomial data occur if the major outcome of an experiment is the classification of experimental ...