Statistical methods for assessing environmental effects on human genetic disorders

Abstract

AbstractMethods are presented for assessing interactions and other effects between genetic and environmental factors for human disease or cancer susceptibility. Statistical estimation and testing approaches are based on a simple multinomial sampling model for the case‐control sampling scenario. It is noted that logistic regression methods can facilitate computation of likelihood‐based statistics in this setting. Additional models for collapsibility over genotypes within the genetic factor are considered. Monte Carlo comparisons show that the method appears to retain nominal significance levels at total sample sizes above 100. At smaller sample sizes, a goodness‐of‐fit statistic is suggested for testing the interactive effect between the genetic and environmental factors.