Calculating Asymptotic Significance Levels of the Constrained Likelihood Ratio Test with Application to Multivariate Genetic Linkage Analysis

Morris Nathan J, Elston Robert and Stein Catherine M
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Morris Nathan J: Case Western Reserve University
Elston Robert: Case Western Reserve University
Stein Catherine M: Case Western Reserve University

Statistical Applications in Genetics and Molecular Biology, 2009, vol. 8, issue 1, 34

Abstract: The asymptotic distribution of the multivariate variance component linkage analysis likelihood ratio test has provoked some contradictory accounts in the literature. In this paper we confirm that some previous results are not correct by deriving the asymptotic distribution in one special case. It is shown that this special case is a good approximation to the distribution in many situations. We also introduce a new approach to simulating from the asymptotic distribution of the likelihood ratio test statistic in constrained testing problems. It is shown that this method is very efficient for small p-values, and is applicable even when the constraints are not convex. The method is related to a multivariate integration problem. We illustrate how the approach can be applied to multivariate linkage analysis in a simulation study. Some more philosophical issues relating to one-sided tests in variance components linkage analysis are discussed.

Keywords: multivariate linkage analysis; variance component testing; nonstandard conditions; constrained hypothesis testing; one-sided testing (search for similar items in EconPapers)
Date: 2009
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DOI: 10.2202/1544-6115.1456

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