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), ])
}
#-----------------------------------------------------------------
