title: A generalized Levene's scale test for variance heterogeneity in the presence of sample correlation and group uncertainty.
abstract: We generalize Levene's test for variance (scale) heterogeneity between k groups for more complex data, when there are sample correlation and group membership uncertainty. Following a two-stage regression framework, we show that least absolute deviation regression must be used in the stage 1 analysis to ensure a correct asymptotic χk-12/(k-1) distribution of the generalized scale (gS) test statistic. We then show that the proposed gS test is independent of the generalized location test, under the joint null hypothesis of no mean and no variance heterogeneity. Consequently, we generalize the recently proposed joint location-scale (gJLS) test, valuable in settings where there is an interaction effect but one interacting variable is not available. We evaluate the proposed method via an extensive simulation study and two genetic association application studies.
authors.affiliation: Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario M5T 3M7, Canada.|Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada.
authors.forename: David
authors.initials: D
authors.lastname: Soave
authors.affiliation: Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario M5T 3M7, Canada.|Department of Statistical Sciences, University of Toronto, Toronto, Ontario M5S 3G3, Canada.
authors.forename: Lei
authors.initials: L
authors.lastname: Sun
mesh_terms: D056726:Genetic Association Studies; D012107:Research Design; D035501:Uncertainty
keywords: Association studies; Heteroscedasticity; Joint location-scale test; Scale test