ArticleStatistical applications in genetics and molecular biology2009
Calculating asymptotic significance levels of the constrained likelihood ratio test with application to multivariate genetic linkage analysis.
Article in Statistical applications in genetics and molecular biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- strum: an R package for structural modeling of latent variables for general pedigrees.BMC genetics · 2015Article
- PLXNA4 is associated with Alzheimer disease and modulates tau phosphorylation.Annals of neurology · 2014Article
- A framework for structural equation models in general pedigrees.Human heredity · 2010Article
- Comparison of univariate and multivariate linkage analysis of traits related to hypertension.BMC proceedings · 2009Article
- Combining information from linkage and association methods.Genetic epidemiology · 2009Article
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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.
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