Dear Jürgen, All the values of your Id variable are equal to 1; how can that make sense? Removing the argument Id=id may get you what you want.
By the way, the document to which you refer was an appendix to a 2002 book that has been superseded by Fox and Weisberg, An R Companion to Applied Regression, Second Edition (Sage, 2011). Appendices for that book are available at <http://socserv.socsci.mcmaster.ca/jfox/Books/Companion/appendix.html>. I hope this helps, John ------------------------------------------------ John Fox Sen. William McMaster Prof. of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ On Sat, 16 Jun 2012 15:04:48 +0200 Jürgen Biedermann <juergen.biederm...@googlemail.com> wrote: > 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.
