R/prederrJM.coxph.R

In JM: Joint Modeling of Longitudinal and Survival Data

prederrJM.coxph <-
function (object, newdata, Tstart, Thoriz, lossFun = c("absolute", "square"), 
                             interval = FALSE, idVar = "id", timeVar = "time", respVar = "y", 
                             evTimeVar = "Time", summary = c("value", "slope", "area"), 
                             tranfFun = function (x) x, ...) {
    if (!inherits(object, "coxph"))
        stop("Use only with 'coxph' objects.\n")
    if (!is.data.frame(newdata) || nrow(newdata) == 0)
        stop("'newdata' must be a data.frame with more than one rows.\n")
    if (is.null(newdata[[idVar]]))
        stop("'idVar' not in 'newdata'.\n")
    lossFun <- if (is.function(lossFun)) {
        lf <- lossFun
        match.fun(lossFun)
    } else {
        lf <- match.arg(lossFun)
        if (lf == "absolute") function (x) abs(x) else function (x) x*x
    }
    summary <- match.arg(summary)
    if (summary %in% c("slope", "area"))
        newdata$area <- newdata$slope <- 0
    id <- newdata[[idVar]]
    id <- match(id, unique(id))
    TermsT <- object$terms
    SurvT <- model.response(model.frame(TermsT, newdata)) 
    Time <- SurvT[, 1]
    newdata2 <- dataLM(newdata, Tstart, idVar, respVar, timeVar, evTimeVar, summary, 
                       tranfFun)
    SurvT <- model.response(model.frame(TermsT, newdata2)) 
    Time <- SurvT[, 1]
    delta <- SurvT[, 2]
    indCens <- Time < Thoriz & delta == 0
    nr <- nrow(newdata2)
    aliveThoriz.id <- newdata2[Time > Thoriz, ]
    Surv.aliveThoriz <- c(summary(survfit(object, newdata = aliveThoriz.id), times = Thoriz)$surv)
    deadThoriz.id <- newdata2[Time <= Thoriz & delta == 1, ]
    Surv.deadThoriz <- c(summary(survfit(object, newdata = deadThoriz.id), times = Thoriz)$surv)
    if (sum(indCens) > 1) {
        censThoriz.id <- newdata2[indCens, ]
        Surv.censThoriz <- c(summary(survfit(object, newdata = censThoriz.id), times = Thoriz)$surv)
        tt <- model.response(model.frame(TermsT, censThoriz.id))[, 1]
        nn <- length(tt)
        weights <- numeric(nn)
        for (i in seq_len(nn)) {
            weights[i] <- c(summary(survfit(object, newdata = censThoriz.id[i, ]), times = Thoriz)$surv) /
                c(summary(survfit(object, newdata = censThoriz.id[i, ]), times = tt[i])$surv)
        }
    } else {
        Surv.censThoriz <- weights <- NA
    }
    prederr <- if (!interval) {
        (1/nr) * sum(lossFun(1 - Surv.aliveThoriz), lossFun(0 - Surv.deadThoriz),
                     weights * lossFun(1 - Surv.censThoriz) + (1 - weights) * lossFun(0 - Surv.censThoriz))
    } else {
        TimeCens <- model.response(model.frame(TermsT, newdata))[, 1]
        deltaCens <- 1 - model.response(model.frame(TermsT, newdata))[, 2]
        KMcens <- survfit(Surv(TimeCens, deltaCens) ~ 1)
        times <- TimeCens[TimeCens > Tstart & TimeCens <= Thoriz & !deltaCens]
        times <- sort(unique(times))
        k <- as.numeric(table(times))
        w <- summary(KMcens, times = Tstart)$surv / summary(KMcens, times = times)$surv
        prederr.times <- sapply(times, 
                                function (t) prederrJM(object, newdata, Tstart, t,
                                                       interval = FALSE, idVar = idVar, timeVar = timeVar,
                                                       respVar = respVar, evTimeVar = evTimeVar, 
                                                       summary = summary, tranfFun = tranfFun)$prederr)
        num <- sum(prederr.times * w * k, na.rm = TRUE)
        den <- sum(w * k, na.rm = TRUE)
        num / den
    }
    out <- list(prederr = prederr, nr = nr, Tstart = Tstart, Thoriz = Thoriz, interval = interval,
                classObject = class(object), nameObject = deparse(substitute(object)), lossFun = lf)
    class(out) <- "prederrJM"
    out
}