title: The power of iterated generalized least squares (GLS) method to detect direct relationships in the analysis of correlated quantitative traits.
abstract: We examined the power of the stepwise iterated generalized least squares (GLS) method by modeling the relationship between quantitative traits and other variables using the simulated data for Problem 2A. The comparison between the generating model provided by the workshop and the results of the stepwise iterated GLS model showed that this method could be used as a first step in identifying the underlying model for genetic data. The estimated covariance matrices also provide useful information about the genetic properties of the traits.
authors.affiliation: Department of Preventive Medicine, University Medical Center at Stony Brook, NY 11794-8036, USA.
authors.forename: Q
authors.initials: Q
authors.lastname: He
authors.forename: B B
authors.initials: BB
authors.lastname: Nemesure
authors.forename: N R
authors.initials: NR
authors.lastname: Mendell
mesh_terms: D003198:Computer Simulation; D005260:Female; D008040:Genetic Linkage; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D019655:Quantitative Trait, Heritable