Nothing
# $Id: residuals.coxph.penal.S 11516 2012-04-24 12:49:14Z therneau $
residuals.coxph.penal <- function(object,
type=c("martingale", "deviance", "score", "schoenfeld",
"dfbeta", "dfbetas", "scaledsch","partial"),
collapse=FALSE, weighted=FALSE, ...) {
type <- match.arg(type)
# Are there any sparse terms, and if so do I need the X matrix?
if (any(object$pterms==2) && !(type=='martingale' || type=='deviance')){
# treat the sparse term as an offset term
# It gets picked up in the linear predictor, so all I need to
# do is "X" it out of the model so that it doesn't get picked up
# as a part of the X matrix and etc.
# I know that the sparse term is a single column BTW
#
sparsename <- (names(object$pterms))[object$pterms==2]
x <- object[['x']] #don't accidentally get object$xlevels
if (is.null(x)) {
temp <- coxph.getdata(object, y=TRUE, x=TRUE, stratax=TRUE)
if (is.null(object$y)) object$y <- temp$y
if (is.null(object$strata)) object$strata <- temp$strata
x <- temp$x
}
object$x <- x[, -match(sparsename, dimnames(x)[[2]]), drop=FALSE]
temp <- attr(object$terms, 'term.labels')
object$terms <- object$terms[-match(sparsename, temp)]
}
NextMethod('residuals')
}
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