R/AdjSpec_AllPoints_none.R

Defines functions AdjSpec_AllPoints_none

AdjSpec_AllPoints_none <- function(diseaseData,
                              controlData,
                              userFormula) {

    outform <- ParseuserFormula(userFormula = userFormula)
    M0 <- eval(parse(text = paste("controlData$",outform[[1]])))
    M1 <- eval(parse(text = paste("diseaseData$",outform[[1]])))
    if (length(outform[[2]]) == 1) {
        expr2 <- paste0("controlData$", outform[[2]])
        expr3 <- paste0("diseaseData$", outform[[2]])
    } else if (length(outform[[2]]) > 1) {
        expr2 <- paste0("controlData[, ", outform[2], "]")
        expr3 <- paste0("diseaseData[, ", outform[2], "]")
    }
    all_Z_C <- eval(parse(text = expr2))
    all_Z_D <- eval(parse(text = expr3))

    rqfit <- NULL
    expr1 <- paste0("rqfit <- rq(", userFormula, ", tau = -1, data = diseaseData)")
    eval(parse(text = expr1))

    all_tau <- rqfit$sol[1, ]
    sens_vec <- 1 - all_tau
    est_b <- rqfit$sol[4:(nrow(rqfit$sol)),]
    control_threshold_q <- as.matrix(cbind(1, all_Z_C)) %*% est_b
    spec_adj = rep(0, length(all_tau))
    spec_adj <- colSums(M0 <= control_threshold_q)/length(M0)

    return(list(sensitivity = sens_vec,
           specificity = spec_adj,
           mono_adj = "none"))

}
ziyili20/caROC documentation built on March 28, 2021, 2:52 a.m.