R/MFr.r

In MF: Mitigated Fraction

#' Mitigated fraction comparing treatment to control.
#' 
#' The mitigated fraction is an estimator that quantifies an intervention's effect on reducing the 
#' severity of a condition. Since its units are on the probability scale, it is often a good idea 
#' to accompany it with an estimator on the original scale of measurement.
#' 
#' @title Mitigated fraction
#' @usage MFr(formula, data, compare = c("con", "vac"))
#' @param formula Formula of the form \code{y ~ x}, where y is a continuous response and x is a factor with two levels
#' @param data Data frame
#' @param compare Text vector stating the factor levels -- \code{compare[1]} is the control or reference group to which \code{compare[2]} is compared
#' @return The estimated mitigated fraction.
#' @export
#' @references Siev D, 2005. An estimator of intervention effect on disease severity. \emph{Journal of Modern Applied Statistical Methods.} 4:500-508
#' @author David Siev
#' @examples
#' MFr(lesion~group,calflung)
#' # [1] 0.44

##--------------------------------------------------------------------
## Simple MF
##--------------------------------------------------------------------
##
MFr <- function(formula, data, compare = c("con", "vac")){
    # formula of form response~treatment
    # x=response for compare[1]
    # y=response for compare[2]
    # compare y to x
    A <- data.frame(model.frame(formula=formula,data=data))
    resp <- A[,1]
    tx <- A[,2]
    x <- resp[tx==compare[1]]
    y <- resp[tx==compare[2]]
    n.x <- length(x)
    n.y <- length(y)
    N <- n.x + n.y
    x.y <- c(x, y)
    w <- sum(rank(x.y)[1.:n.x])
    return(((2. * w - n.x * (1. + n.x + n.y))/(n.x * n.y)))
}