Assess risk stratification performance

risk.stratification.analysis <- function(x)
{
    ## Purpose: Assess risk stratification performance. 
    ## Arguments:
    ##   x: a numeric vector of length 2K for the raw confusion matrix.
    ##      First K numbers: count of each risk group with reference positive results
    ##      Second K numbers: count of each risk group with reference negative results
    ## Return:
    ##   an expanded confusion matrix with post-test disease risks and likelihood ratios.
    ## Author: Feiming Chen
    ## ________________________________________________

    d <- as.data.frame(addmargins(matrix(x, ncol = 2)))
    n <- nrow(d) - 1                    # number of risk groups
    g.names <- paste0("Group ", 1:n)    # group names
    dimnames(d) <- list(c(g.names, "Sum"), c("Ref.Pos", "Ref.Neg", "Sum"))

    d$Post.Test.Risk <- with(d, Ref.Pos / Sum, 2)
    d$Likelihood.Ratio <- with(d, Ref.Pos / Ref.Pos[n+1] / (Ref.Neg / Ref.Neg[n+1]))

    d
}
if (F) {                                # Unit Test
    x <- c(38, 27, 35, 5, 10, 41, 137, 158)
    risk.stratification.analysis(x)

    ##         Ref.Pos Ref.Neg Sum Post.Test.Risk Likelihood.Ratio
    ## Group 1      38      10  48           0.79            12.52
    ## Group 2      27      41  68           0.40             2.17
    ## Group 3      35     137 172           0.20             0.84
    ## Group 4       5     158 163           0.03             0.10
    ## Sum         105     346 451           0.23             1.00

}