title: A simulation study of permutation, bootstrap, and gene dropping for assessing statistical significance in the case of unequal relatedness.
abstract: We used simulations to evaluate methods for assessing statistical significance in association studies. When the statistical model appropriately accounted for relatedness among individuals, unrestricted permutation tests and a few other simulation-based methods effectively controlled type I error rates; otherwise, only gene dropping controlled type I error but at the expense of statistical power.
authors.affiliation: Department of Human Genetics, the University of Chicago, Chicago, IL 60637, USA.
authors.forename: Riyan
authors.initials: R
authors.lastname: Cheng
authors.forename: Abraham A
authors.initials: AA
authors.lastname: Palmer
mesh_terms: D003198:Computer Simulation; D014644:Genetic Variation; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D010375:Pedigree; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics*