I am testing the association between a gene and a binary disease. The gene has many different "versions". These versions are called alleles.I am also including covariates for sex, age, etc.
Right now I am doing a logistic regression-based omnibus test for the gene like this (pseudocode):
full<- "disease ~ sex + age + allele1 + allele2 + allele3" null<- "disease ~ sex + age" anova(null, full, test='Chisq')
I think I realize I could follow omnibus with the wald test to determine how significant each allele is, but I am wondering if this is best done with the LR test, which would allow me to account for the covariates on each allele comparisons, like this:
full1<- "disease ~ sex + age + allele1" null<- "disease ~ sex + age" anova(null, full1, test='Chisq') full2<- "disease ~ sex + age + allele2" null<- "disease ~ sex + age" anova(null, full2, test='Chisq')
My gut feeling is that the LR approach would be better for by allele comparisons, because of the inclusion of covariates. Is this the case?