On dichotomizing phenotypes in family-based association tests: quantitative phenotypes are not always the optimal choice.
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.
Fardo
David
D
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. dfardo@hsph.farvard.edu
Celedón
Juan C
JC
Raby
Benjamin A
BA
Weiss
Scott T
ST
Lange
Christoph
C
D000483:Alleles; D001249:Asthma / Q000235:genetics / Q000503:physiopathology; D002648:Child; D005190:Family; D005260:Female; D005541:Forced Expiratory Volume; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D005821:Genetic Techniques; D006801:Humans; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D010641:Phenotype; D019655:Quantitative Trait, Heritable