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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Rcode.r
\name{rstrans}
\alias{rstrans}
\title{Fit Cox Proportional Hazards Model in Transformed Time}
\usage{
rstrans(
formula = formula(data),
data = parent.frame(),
ratetable = relsurv::slopop,
int,
na.action,
init,
control,
rmap,
...
)
}
\arguments{
\item{formula}{a formula object, with the response as a \code{Surv} object
on the left of a \code{~} operator, and, if desired, terms separated by the
\code{+} operator on the right.
NOTE: The follow-up time must be in days.}
\item{data}{a data.frame in which to interpret the variables named in the
\code{formula}.}
\item{ratetable}{a table of event rates, such as \code{slopop}.}
\item{int}{the number of follow-up years used for calculating survival(the
rest is censored). If missing, it is set the the maximum observed follow-up
time.}
\item{na.action}{a missing-data filter function, applied to the model.frame,
after any subset argument has been used. Default is
\code{options()$na.action}.}
\item{init}{vector of initial values of the iteration. Default initial
value is zero for all variables.}
\item{control}{a list of parameters for controlling the fitting process.
See the documentation for \code{coxph.control} for details.}
\item{rmap}{an optional list to be used if the variables are not organized
and named in the same way as in the \code{ratetable} object. See details
below.}
\item{...}{other arguments will be passed to \code{coxph.control}.}
}
\value{
an object of class \code{coxph}. See \code{coxph.object} and
\code{coxph.detail} for details. \item{y}{ an object of class \code{Surv}
containing the transformed times (these times do not depend on covariates).
}
}
\description{
The function transforms each person's time to his/her probability of dying
at that time according to the ratetable. It then fits the Cox proportional
hazards model with the transformed times as a response. It can also be used
for calculatin the transformed times (no covariates are needed in the
formula for that purpose).
}
\details{
NOTE: The follow-up time must be specified in days. The \code{ratetable}
being used may have different variable names and formats than the user's
data set, this is dealt with by the \code{rmap} argument. For example, if
age is in years in the data set but in days in the \code{ratetable} object,
age=age*365.241 should be used. The calendar year can be in any date format
(Date and POSIXt are allowed), the date formats in the
\code{ratetable} and in the data may differ. A side product of this
function are the transformed times - stored in teh \code{y} object of the
output. To get these times, covariates are of course irrelevant.
}
\examples{
data(slopop)
data(rdata)
#fit a Cox model using the transformed times
#note that the variable year is given in days since 01.01.1960 and that
#age must be multiplied by 365.241 in order to be expressed in days.
fit <- rstrans(Surv(time,cens)~sex+as.factor(agegr),rmap=list(age=age*365.241,
sex=sex,year=year),ratetable=slopop,data=rdata)
#check the goodness of fit
rs.br(fit)
}
\references{
Method: Stare J., Henderson R., Pohar M. (2005) "An individual
measure for relative survival." Journal of the Royal Statistical Society:
Series C, \bold{54} 115--126.
Package. Pohar M., Stare J. (2006) "Relative survival analysis in R."
Computer Methods and Programs in Biomedicine, \bold{81}: 272--278
Relative survival: Pohar, M., Stare, J. (2007) "Making relative survival
analysis relatively easy." Computers in biology and medicine, \bold{37}:
1741--1749.
}
\seealso{
\code{\link{rsmul}}, \code{\link{invtime}}, \code{\link{rsadd}},
\code{\link[survival:survexp]{survival::survexp}}.
}
\keyword{survival}
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