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Vol. 57, No. 1, 2004   

Free Abstract     Article (References)     Article (PDF 81 KB)     

Original Paper

Power Loss for Linkage Analysis due to the Dichotomization of Trichotomous Phenotypes
Jonathan Corbetta, C. Charles Gua, John P. Ricea,b, Theodore Reichb,c, Michael A. Provincea, D.C. Raoa,b,c

aDivision of Biostatistics, Departments of
bPsychiatry, and
cGenetics, Washington University School of Medicine, St.Louis,Mo., USA

Address of Corresponding Author

Hum Hered 2004;57:21-27 (DOI: 10.1159/000077386)


 goto top of page Key Words

  • Linkage
  • Power
  • Polychotomous trait

 goto top of page Abstract

Objectives: Some traits, while naturally polychotomous, are routinely dichotomized for genetic analysis. Dichotomization, intuitively, leads to a loss of power to detect linkage, as some phenotypic variability is discarded. This paper examines this power loss in the context of a trichotomous trait. Methods: To examine this power loss, we performed a simulation study where a trichotomous trait was simulated in a sample of 1,000 sib-pairs under various genetic models. The study was replicated 1,000 times. Linkage analysis using a variance components method, as implemented in Mx, was then performed on the trichotomous trait and compared with that on a dichotomized version of the trait. Results: A comparison of the power and false positive rates of the analyses shows that power to detect linkage was increased by up to 22 percentage points simply by examining the trait as a trichotomy instead of a dichotomy. Under all models examined, the trichotomous analysis outperformed the dichotomous version. Conclusions: Comparable levels of false positive rates under both methods confirm that this power gain comes solely from the information lost upon dichotomization. Thus, dichotomizing tri- or poly-chotomous traits can lead to crippling power loss, especially in the case of many loci of small effect.

Copyright © 2004 S. Karger AG, Basel


 goto top of page Author Contacts

Jonathan Corbett, PhD
Division of Biostatistics, Washington University School of Medicine
Box 8067, 660 S. Euclid Ave.
St. Louis, MO 63110 (USA)
Tel. +1 314 362 3593, Fax +1 314 362 2693, E-Mail jon@wubios.wustl.edu


 goto top of page Article Information

Received: May 21, 2003
Accepted after revision: October 30, 2003
Number of Print Pages : 7
Number of Figures : 0, Number of Tables : 4, Number of References : 17

 
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