Some Improved Tests for Multivariate One-Sided Hypotheses

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Some Improved Tests for Multivariate One-Sided Hypotheses

TitleSome Improved Tests for Multivariate One-Sided Hypotheses
Publication TypeJournal Article
Year of Publication2006
AuthorsPerlman, MD, WU, LANG
JournalMetrika
Volume64
Pagination23–39
Date Publishedfeb
ISSN0026-1335, 1435-926X
KeywordsEconomic Theory, general, likelihood ratio test, Multiple endpoints, One-sided hypothesis, p-value, Probability Theory and Stochastic Processes, Statistics, Statistics for Business/Economics/Mathematical Finance/Insurance, Union-intersection test
AbstractMultivariate one-sided hypothesis-testing problems are very common in clinical trials with multiple endpoints. The likelihood ratio test (LRT) and union-intersection test (UIT) are widely used for testing such problems. It is argued that, for many important multivariate one-sided testing problems, the LRT and UIT fail to adapt to the presence of subregions of varying dimensionalities on the boundary of the null parameter space and thus give undesirable results. Several improved tests are proposed that do adapt to the varying dimensionalities and hence reflect the evidence provided by the data more accurately than the LRT and UIT. Moreover, the proposed tests are often less biased and more powerful than the LRT and UIT.
URLhttp://link.springer.com/article/10.1007/s00184-006-0028-0
DOI10.1007/s00184-006-0028-0