title: Lipid data from NHLBI veteran twins: interpreting genetic analyses when model assumptions fail.
abstract: Analyses were performed on lipid data from the NHLBI Veteran Twin Study. The analyses focused on longitudinal multivariate models, describing how the genetic effects on lipids vary over time. Our pedigree-based model selection approach allows simultaneous estimation of both covariance structure parameters and regression parameters. The analyses reveal strong correlations between additive genetic effects over time, implying that genetic effects on lipids are somewhat constant throughout the life span represented within this sample. Both univariate preliminary analyses and robust fitting applied to the longitudinal models indicate that several assumptions underlying the twin analyses are violated. Although variance component and correlation parameter estimates are not much changed by robust fitting analyses, questions remain about the behavior of parameter estimates in multivariate genetic models under departures from model assumptions.
authors.affiliation: Department of Mathematics and Statistics, University of Idaho, Moscow 83844.
authors.forename: C J
authors.initials: CJ
authors.lastname: Williams
authors.forename: U W
authors.initials: UW
authors.lastname: Wijesiri
mesh_terms: D006801:Humans; D016013:Likelihood Functions; D008055:Lipids / Q000235:genetics*; D008297:Male; D008957:Models, Genetic; D009316:National Institutes of Health (U.S.); D014429:Twins, Dizygotic / Q000706:statistics & numerical data*; D014430:Twins, Monozygotic / Q000706:statistics & numerical data*; D014481:United States; D014728:Veterans / Q000706:statistics & numerical data*; D014857:Warfare
chemical_list: D008055:Lipids