Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Sanguinetti, Guido


IMPACT FACTOR 2018: 0.536
5-year IMPACT FACTOR: 0.764

CiteScore 2018: 0.49

SCImago Journal Rank (SJR) 2018: 0.316
Source Normalized Impact per Paper (SNIP) 2018: 0.342

Mathematical Citation Quotient (MCQ) 2017: 0.04

Online
ISSN
1544-6115
See all formats and pricing
More options …
Volume 8, Issue 1

Issues

Volume 10 (2011)

Volume 9 (2010)

Volume 6 (2007)

Volume 5 (2006)

Volume 4 (2005)

Volume 2 (2003)

Volume 1 (2002)

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

Nathan J Morris / Robert Elston / Catherine M Stein
Published Online: 2009-09-17 | DOI: https://doi.org/10.2202/1544-6115.1456

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

About the article

Published Online: 2009-09-17


Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 8, Issue 1, Pages 1–32, ISSN (Online) 1544-6115, DOI: https://doi.org/10.2202/1544-6115.1456.

Export Citation

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston.Get Permission

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

[1]
Yeunjoo E Song, Catherine M Stein, and Nathan J Morris
BMC Genetics, 2015, Volume 16, Number 1
[2]
Nathan J. Morris, Robert C. Elston, and Catherine M. Stein
Human Heredity, 2010, Volume 70, Number 4, Page 278
[3]
Elizabeth E. Marchani, Andrea Callegaro, E. Warwick Daw, and Ellen M. Wijsman
Genetic Epidemiology, 2009, Volume 33, Number S1, Page S81
[4]
Gyungah Jun, Hirohide Asai, Ella Zeldich, Elodie Drapeau, CiDi Chen, Jaeyoon Chung, Jong-Ho Park, Sehwa Kim, Vahram Haroutunian, Tatiana Foroud, Ryozo Kuwano, Jonathan L. Haines, Margaret A. Pericak-Vance, Gerard D. Schellenberg, Kathryn L. Lunetta, Jong-Won Kim, Joseph D. Buxbaum, Richard Mayeux, Tsuneya Ikezu, Carmela R. Abraham, and Lindsay A. Farrer
Annals of Neurology, 2014, Volume 76, Number 3, Page 379
[5]
Gengxin Li and Yuehua Cui
Journal of Statistical Planning and Inference, 2016, Volume 178, Page 70

Comments (0)

Please log in or register to comment.
Log in