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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))