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

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

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.

Submitted: March 3, 2009 · Accepted: August 21, 2009 · Published: September 17, 2009

Recommended Citation

Morris, Nathan J.; Elston, Robert; and Stein, Catherine M. (2009) "Calculating Asymptotic Significance Levels of the Constrained Likelihood Ratio Test with Application to Multivariate Genetic Linkage Analysis," Statistical Applications in Genetics and Molecular Biology: Vol. 8 : Iss. 1, Article 39.
DOI: 10.2202/1544-6115.1456
Available at: http://www.bepress.com/sagmb/vol8/iss1/art39

 
 
 
 

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