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#SCCS @(#)residuals.coxph.s 4.5 7/14/92
residuals.cph <-
function(object, type=c("martingale", "deviance", "score", "schoenfeld",
"dfbeta","dfbetas", "scaledsch"), collapse=FALSE, weighted=FALSE, ...)
{
type <- match.arg(type)
if(.R.) require('survival')
otype <- type
if(type=="dfbeta" | type=="dfbetas") type <- "score"
if(type=="scaledsch") type <- "schoenfeld"
n <- length(object$residuals)
rr <- object$residual
y <- object$y
x <- object$x
weights <- object$weights
strat <- attr(x,"strata")
method <- object$method
if (method=='exact' && (type=='score' || type=='schoenfeld'))
stop(paste(type, 'residuals are not available for the exact method'))
if(type!="martingale" & is.null(x))
stop("you must specify x=T in the fit")
if(type!="deviance" & type!="martingale" & is.null(y))
stop("you must specify y=T in the fit")
if(type!="martingale") {
ny <- ncol(y)
status <- y[,ny,drop=TRUE]
if (type != 'deviance') {
nvar <- ncol(x)
if (is.null(strat)) {
ord <- order(y[,ny-1], -status)
newstrat <- rep(0,n)
}
else {
ord <- order(strat, y[,ny-1], -status)
newstrat <- c(diff(as.numeric(strat[ord]))!=0 ,1)
}
newstrat[n] <- 1
# sort the data
x <- x[ord,]
y <- y[ord,]
score <- exp(object$linear.predictor)[ord]
weights <- if(length(weights)) weights[ord] else rep(1,n)
if (ny ==3) subs <- paste("agres", 1:2, sep='')
else subs <- paste("coxres",1:2, sep='')
}
}
#
# Now I have gotten the data that I need-- do the work
#
if (type=='schoenfeld') {
if (ny==2) {
mintime <- min(y[, 1])
if(mintime < 0) y <- cbind(2 * mintime - 1, y)
else y <- cbind(-1, y)
}
temp <- if(.R.)
.C("coxscho",
n=as.integer(n),
as.integer(nvar),
as.double(y),
resid= x,
score * weights,
as.integer(newstrat),
as.integer(method=='efron'),
double(3*nvar), PACKAGE="survival") else
.C(if(.SV4.)'S_coxscho' else "coxscho", ##14Nov00
n=as.integer(n),
as.integer(nvar),
as.double(y),
resid= x,
score * weights,
as.integer(newstrat),
as.integer(method=='efron'),
double(3*nvar))
deaths <- y[,3]==1
if (nvar==1) rr <- temp$resid[deaths]
else rr <- matrix(temp$resid[deaths,], ncol=nvar) #pick rows, and kill attr
if (length(object$strata))
attr(rr, "strata") <- table((strat[ord])[deaths])
time <- c(y[deaths,2]) # 'c' kills all of the attributes
if (is.matrix(rr)) dimnames(rr)<- list(time, names(object$coef))
else names(rr) <- time
if (otype=='scaledsch') {
ndead <- sum(deaths)
coef <- ifelse(is.na(object$coef), 0, object$coef)
if (nvar==1) rr <- rr*object$var * ndead + coef
else rr <- rr %*% object$var * ndead +
outer(rep(1,nrow(rr)), coef)
}
return(rr)
}
if (type=='score') {
if (ny==2) {
resid <- if(.R.)
.C("coxscore",
as.integer(n),
as.integer(nvar),
as.double(y),
x=as.double(x),
as.integer(newstrat),
as.double(score),
as.double(weights),
as.integer(method=='efron'),
resid= double(n*nvar),
double(2*nvar), PACKAGE="survival")$resid else
.C(if(.SV4.)'S_coxscore' else "coxscore",
as.integer(n),
as.integer(nvar),
as.double(y),
x=as.double(x),
as.integer(newstrat),
as.double(score),
as.double(weights),
as.integer(method=='efron'),
resid= double(n*nvar),
double(2*nvar))$resid
}
else {
resid <- if(.R.)
.C("agscore",
as.integer(n),
as.integer(nvar),
as.double(y),
as.double(x),
as.integer(newstrat),
as.double(score),
as.double(weights),
as.integer(method=='efron'),
resid=double(n*nvar),
double(nvar*6), PACKAGE="survival")$resid
.C(if(.SV4.)'S_agscore' else "agscore",
as.integer(n),
as.integer(nvar),
as.double(y),
as.double(x),
as.integer(newstrat),
as.double(score),
as.double(weights),
as.integer(method=='efron'),
resid=double(n*nvar),
double(nvar*6))$resid
}
if (nvar >1) {
rr <- matrix(0, n, nvar)
rr[ord,] <- matrix(resid, ncol=nvar)
dimnames(rr) <- list(names(object$resid), names(object$coef))
}
else rr[ord] <- resid
}
#Expand out the missing values in the result
if (!is.null(object$na.action)) {
rr <- naresid(object$na.action, rr)
if (is.matrix(rr)) n <- nrow(rr)
else n <- length(rr)
if (type=='deviance') status <- naresid(object$na.action, status)
}
# Collapse if desired
if (!missing(collapse)) {
if (length(collapse) !=n) stop("Wrong length for 'collapse'")
rr <- rowsum(rr, collapse)
}
# Deviance residuals are computed after collapsing occurs
if (type=='deviance')
rr <- sign(rr) *sqrt(-2* (rr+
ifelse(status==0, 0, status*logb(status-rr))))
if (otype=='dfbeta') rr %*% object$var
else if (otype=='dfbetas') (rr %*% object$var) %*%
diag(sqrt(1/diag(object$var)))
else rr
}
|
