In family-based association studies, quantitative traits are thought to provide higher statistical power than dichotomous traits. Consequently, it is standard practice to collect quantitative traits and to analyze them as such. However, in many situations, continuous measurements are more difficult to obtain and/or need to be adjusted for other factors/confounding variables which also have to be measured. In such scenarios, it can be advantageous to record and analyze a "simplified/dichotomized" version of the original trait. Under fairly general circumstances, we derive here rules for the dichotomization of quantitative traits that maintain power levels that are comparable to the analysis of the original quantitative trait. Using simulation studies, we show that the proposed rules are robust against phenotypic misclassification, making them an ideal tool for inexpensive phenotyping in large-scale studies. The guidelines are illustrated by an application to an asthma study.
On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice. Publishing Authors By Initials
On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice. Journal Published:
PUBLICATION TYPE: Research Support, N.I.H., Extr
Journal: Genetic epidemiology
VOLUME: 31
Page Numbers: 376-82
Journal Abbreviation: Genet. Epidemiol.
ISSN: 0741-0395
DAY: 3
MONTH: Jul
YEAR: 2007
On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice. Information
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LANGUAGE: eng
NlmUniqueID: 8411723
On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice. Keywords Mesh Terms:
KEYWORDS: Quantitative Trait, Heritable
MESH TERMS: physiopathology
Chemical & Substance for Abstract: On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice. Information
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Grant and Affiliation Information for On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice.
AFFILIATION: Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. dfardo@hsph.farvard.edu
Country: United States
AGENCY: United States NIDDK
GRANT: T90 DK070078
ACRONYM: DK
MEDLINETA: Genet Epidemiol
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