Inference about a secondary process following a sequential trial

W. J. Hall; Benjamin Yakir

doi:10.1093/biomet/90.3.597

Inference about a secondary process following a sequential trial

W. J. Hall^*, Benjamin Yakir

^*Corresponding author for this work

Department of Statistics

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We consider the following sequential testing problem. A group-sequential or fully-sequential test is carried out for a primary parameter, using a score process or an effective score process to eliminate nuisance parameters. After stopping, the possibility of additional parameters is considered, and appropriate tests and estimators are desired that recognise the sequential stopping rule. We formulate an asymptotic multi-dimensional Gaussian process form of such problems, and then construct tests and confidence procedures. Optimality conditions are given, and an example is summarised.

Original language	English
Pages (from-to)	597-611
Number of pages	15
Journal	Biometrika
Volume	90
Issue number	3
DOIs	https://doi.org/10.1093/biomet/90.3.597
State	Published - Sep 2003

Bibliographical note

Funding Information:
The M trial stimulated the research reported here; we thank Dr Arthur Moss and CPI/Guidant for leadership and sponsorship of this trial. The research reported here was supported by a grant from the U.S. National Heart, Lung, and Blood Institute.

Keywords

Clinical trial
Gaussian process
Median-unbiased estimator
Testing for interaction
Unbiased test

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10.1093/biomet/90.3.597

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AU - Yakir, Benjamin

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N2 - We consider the following sequential testing problem. A group-sequential or fully-sequential test is carried out for a primary parameter, using a score process or an effective score process to eliminate nuisance parameters. After stopping, the possibility of additional parameters is considered, and appropriate tests and estimators are desired that recognise the sequential stopping rule. We formulate an asymptotic multi-dimensional Gaussian process form of such problems, and then construct tests and confidence procedures. Optimality conditions are given, and an example is summarised.

AB - We consider the following sequential testing problem. A group-sequential or fully-sequential test is carried out for a primary parameter, using a score process or an effective score process to eliminate nuisance parameters. After stopping, the possibility of additional parameters is considered, and appropriate tests and estimators are desired that recognise the sequential stopping rule. We formulate an asymptotic multi-dimensional Gaussian process form of such problems, and then construct tests and confidence procedures. Optimality conditions are given, and an example is summarised.

KW - Clinical trial

KW - Gaussian process

KW - Median-unbiased estimator

KW - Testing for interaction

KW - Unbiased test

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Inference about a secondary process following a sequential trial

Abstract

Bibliographical note

Keywords

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