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Statistical methods for assessing environmental effects on human genetic disorders
Author(s) -
Piegorsch Walter W.,
Taylor Jack A.
Publication year - 1992
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.3170030402
Subject(s) - statistics , multinomial logistic regression , statistic , sample size determination , logistic regression , sampling (signal processing) , econometrics , test statistic , goodness of fit , monte carlo method , computer science , sample (material) , statistical hypothesis testing , mathematics , chemistry , filter (signal processing) , chromatography , computer vision
Methods 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.