Dear Mr. Therneau, Mr. Fox, or to whoever, who has some time...
I don't find a solution to use the "survfit" function (package:
survival) for a defined pattern of covariates with a Cox-Model
including a time dependent interaction term. Somehow the definition of
my "newdata" argument seems to be erroneous.
I already googled the problem, found many persons having the same or a
similar problem, but still no solution.
I want to stress that my time-dependent covariate does not depend on the
failure of an individual (in this case it doesn't seem sensible to
predict a survivor function for an individual). Rather one of my effects
declines with time (time-dependent coefficient).
For illustration, I use the example of John Fox's paper "Cox
Proportional - Hazards Regression for Survival Data".
http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-cox-regression.pdf
Do you know any help? See code below
Thanks very much in advance
Jürgen Biedermann
#----------------------------------------
#Code
Rossi <-
read.table("http://cran.r-project.org/doc/contrib/Fox-Companion/Rossi.txt";,
header=T)
Rossi.2 <- fold(Rossi, time='week',
event='arrest', cov=11:62, cov.names='employed')
# see below for the fold function from John Fox
# modeling an interaction with time (Page 14)
mod.allison.5 <- coxph(Surv(start, stop, arrest.time) ~
fin + age + age:stop + prio,
data=Rossi.2)
mod.allison.5
# Attempt to get the survivor function of a person with age=30, fin=0
and prio=5
newdata.1 <-
data.frame(unique(Rossi.2[c("start","stop")]),fin=0,age=30,prio=5,Id=1,arrest.time=0)
fit <- survfit(mod.allison.5,newdata.1,id="Id")
Error message:
>Fehler in model.frame.default(data = newdata.1, id = "Id", formula =
Surv(start, :
Variablenlängen sind unterschiedlich (gefunden für '(id)')
--> failure, length of variables are different.
#-----------------------------------------------------------------
fold <- function(data, time, event, cov,
cov.names=paste('covariate', '.', 1:ncovs, sep=""),
suffix='.time', cov.times=0:ncov, common.times=TRUE, lag=0){
vlag <- function(x, lag) c(rep(NA, lag), x[1:(length(x)-lag)])
xlag <- function(x, lag) apply(as.matrix(x), 2, vlag, lag=lag)
all.cov <- unlist(cov)
if (!is.list(cov)) cov <- list(cov)
ncovs <- length(cov)
nrow <- nrow(data)
ncol <- ncol(data)
ncov <- length(cov[[1]])
nobs <- nrow*ncov
if (length(unique(c(sapply(cov, length), length(cov.times)-1))) > 1)
stop(paste(
"all elements of cov must be of the same length and \n",
"cov.times must have one more entry than each element of
cov."))
var.names <- names(data)
subjects <- rownames(data)
omit.cols <- if (!common.times) c(all.cov, cov.times) else all.cov
keep.cols <- (1:ncol)[-omit.cols]
nkeep <- length(keep.cols)
if (is.numeric(event)) event <- var.names[event]
times <- if (common.times) matrix(cov.times, nrow, ncov+1, byrow=T)
else data[, cov.times]
new.data <- matrix(Inf, nobs, 3 + ncovs + nkeep)
rownames <- rep("", nobs)
colnames(new.data) <- c('start', 'stop', paste(event, suffix, sep=""),
var.names[-omit.cols], cov.names)
end.row <- 0
for (i in 1:nrow){
start.row <- end.row + 1
end.row <- end.row + ncov
start <- times[i, 1:ncov]
stop <- times[i, 2:(ncov+1)]
event.time <- ifelse (stop == data[i, time] & data[i, event] ==
1, 1, 0)
keep <- matrix(unlist(data[i, -omit.cols]), ncov, nkeep, byrow=T)
select <- apply(matrix(!is.na(data[i, all.cov]), ncol=ncovs),
1, all)
rows <- start.row:end.row
cov.mat <- xlag(matrix(unlist(data[i, all.cov]),
nrow=length(rows)), lag)
new.data[rows[select], ] <-
cbind(start, stop, event.time, keep, cov.mat)[select,]
rownames[rows] <- paste(subjects[i], '.', seq(along=rows), sep="")
}
row.names(new.data) <- rownames
as.data.frame(new.data[new.data[, 1] != Inf &
apply(as.matrix(!is.na(new.data[, cov.names])), 1, all), ])
}
#-----------------------------------------------------------------
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
