RDocumentation: snp.logistic

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if(!require('CGEN')) {
    install.packages('CGEN')
    library('CGEN')
}

 # Use the ovarian cancer data
 data(Xdata, package="CGEN")

 # Fit using a stratification (categorical) variable
 ret <- snp.logistic(Xdata, "case.control", "BRCA.status",
                     main.vars=c("oral.years", "n.children"), 
                     int.vars=c("oral.years", "n.children"), 
                     strata.var=~factor(ethnic.group))

 # Compute a summary table for the models
 getSummary(ret)

 # Compute a Wald test for the main effect of the SNP and interaction
 getWaldTest(ret, c("BRCA.status", "BRCA.status:oral.years", "BRCA.status:n.children"))

 # Fit the same model as above using formulas
 ret2 <- snp.logistic(Xdata, "case.control", "BRCA.status",
                     main.vars=~oral.years + n.children, 
                     int.vars=~oral.years + n.children, 
                     strata.var=~factor(ethnic.group))