title: Comparison of multivariate tests for genetic linkage.
abstract: OBJECTIVE
  Multivariate tests for linkage can provide improved power over univariate tests but the type I error rates and comparative power of commonly used methods have not previously been compared. Here we studied the behavior of bivariate formulations of the variance component (VC) and Haseman-Elston (H-E) approaches.
  
  
  METHODS
  We compared through simulation studies the bivariate H-E test with the unconstrained bivariate VC approach and with a VC approach in which the major-gene correlation is constrained to +/-1. We also compared these methods to univariate methods.
  
  
  RESULTS
  Bivariate approaches are more powerful than univariate analyses unless the traits are very highly positively correlated. The power of the bivariate H-E test was less than the VC procedures. The constrained test was often less powerful than the unconstrained test. The empirical distributions of the bivariate H-E test and the unconstrained bivariate VC test conformed with asymptotic distributions for samples of 100 or more sibships of size 4.
  
  
  CONCLUSIONS
  The unconstrained VC test is valuable for testing for preliminary linkages using multivariate phenotypes. The bivariate H-E test was less powerful than the bivariate VC tests.
authors.affiliation: Departments of Epidemiology and Biomathematics, The University of Texas M.D. Anderson Cancer Center, Houston, Tex., USA. camos@request.mdacc.tmc.edu
authors.forename: C
authors.initials: C
authors.lastname: Amos
authors.forename: M
authors.initials: M
authors.lastname: de Andrade
authors.forename: D
authors.initials: D
authors.lastname: Zhu
mesh_terms: D003198:Computer Simulation; D008040:Genetic Linkage; D008957:Models, Genetic; D015233:Models, Statistical; D015999:Multivariate Analysis