similar to: further notes on model.frame issue

The survexp function can fail when called from another function. The "why" of this has me baffled, however. Here is a simple test case, using a very stripped down version of survexp: survexp.test <- function(formula, data, weights, subset, na.action, rmap, times, cohort=TRUE, conditional=FALSE, ratetable=survexp.us, scale=1, npoints, se.fit,

Hello, I probably have a syntax error in trying to generate an expected survival curve from a weighted cox model, but I can't see it. I used the help sample code to generate a weighted model, with the addition of a "weights=albumin" argument (I only chose albumin because it had no missing values, not because of any real relevance). Below are my code with the resulting error

Dear All, reposting, because I did not find a solution, maybe someone could check the example below. It's taken from the help page of survdiff. Executing it, gives the error "Error in floor(temp) : Non-numeric argument to mathematical function" best regards, Heinz library(survival) ## Example from help page of survdiff ## Expected survival for heart transplant patients based

survexp in survival5 doesn't seem to work for me. see below: > library(survival5) Attaching Package "package:survival5": The following object(s) are masked from package:base : sort.list > library(chron) > data(ratetables) > survexp(~ratetable(year=julian(6,1,1991), + sex=1,age=35*365.24),times=(0:30)/6*365.24) Error in as.character(as.date(c(min(R[, 3]),

Dear all, I am having a (really) hard time getting pyears to work together with a ratetable to give me the number of expected events (deaths). I have the following data: dos, date of surgery, as.Date dof, date of last follow-up, as.Date dos, date of surgery, as.Date sex, gender, as.factor (female,male) ev, event(death), 0= censored at time point dof, 1=death at time point dof Could someone

Dear All, Does someone have, or know of survexp ratetables for european contries, especially Austria and Germany? I know only about slopop in the package relsurv. Thanks in advance Heinz T??chler

Dear All, when I try to reproduce an example of survexp, taken from the help page of survdiff, I receive the error message "Error in floor(temp) : Non-numeric argument to mathematical function" . It seems to come from match.ratetable. I think, it has to do with character variables in a ratetable. I would be interested to know, if it works for others. With an older version of

> Several changes in print.survfit, plot.survfit and seemingly in the structure > of ratetabels effect some of my syntax files. > Is there somewhere a documentation of these changes, besides the code itself? I agree, the Changelog.09 file is not as comprehensive as one would like. Specific comments: 1. The ratetables were recently changed to accomodate a new option. I thought

The model.frame function has trouble with a certain type of really long formula. Here is a test: tname <- paste('var', 1:50, sep='') tmat <- matrix(rnorm(500), ncol=50, dimnames=list(NULL, tname)) tdata <- data.frame(tmat) temp1 <- paste( paste(tname, tname, sep='='), collapse=', ') temp2 <- paste("~1 + cbind(", temp1, ")")

Hello, I am interested in producing the expected number of events, in a recurring events setting. I am using the Andersen-Gill model, as fit by the function "coxph" in the package "survival." I need to produce expected numbers of events for a cohort, cumulatively, at several fixed times. My ultimate goal is: To fit an AG model to a reference sample, then use that fitted model

Hello, I'm attempting to use the ratetable argument to survexp in the survival package. I use the example from the ?survexp help page below, and then slightly modify it to produce an error. library(survival) data(pbc) #fit a model without any factors pfit1 <- coxph(Surv(time, status > 0) ~ trt + log(bili) + log(protime) + age + platelet, data=pbc) #this works as expected

Hello, and thank you in advance. I would like to capture the expected survival from a coxph model for subjects in an observational study with recurrent events, but the survexp statement is failing due to memory. I am using R version 2.13.1 (2011-07-08) on Windows XP. My objective is to plot the fitted survival with the Kaplan-Meier plot. Below is the code with output and [unfortunately]

I am not sure if this is the right place for that kind of questions, but I wondered that the recommended package survival did not pass R's check procedure without warnings: 1) unbalanced braces: * Rd files with unbalanced braces: * man/Surv.Rd * man/cluster.Rd * man/cox.zph.Rd * man/coxph.Rd * man/coxph.detail.Rd * man/date.ddmmmyy.Rd * man/lines.survfit.Rd *

Well, I would suggest using the code already in place in the survival package. Here is my code for your problem. I'm using a copy of the larynx data as found from the web resources for the Klein and Moeschberger book. larynx <- read.table("larynx.dat", skip=12, col.names=c("stage", "time", "age", "year",

Dear R-users, I have a couple of questions about the relsurv package: 1) when I try to run the example: fit <- rsmul(Surv(time,cens)~sex+as.factor(agegr)+ratetable(age=age*365.24,sex=sex,year=year),ratetable=slopop,data=rdata) with the datasets in the package (rdata and slopop) it gives me an error: Error in nrow(x) : object "x" not found 2) If I have a date format

Hi All, I am relatively new to R (took a class 2 yrs ago ...), and am hoping someone can point me in the right direction for a problem I'd like to solve in R : I would like to calculate the relative mortality of a particular impairment, relative to the standard population. I.e. I'm trying to find S_relative(t) in the eqn below : S_impar(t) = S_standard(t) * S_relative(t) where

Hi R users, I'm using the survey package to calculate summary statistics for a large health survey (the Demographic and Health Survey for Honduras, 2006), and when I try to calculate the variances for several variables, I get negative numbers. I thought it may be my data, so I ran the example on the help page: data(api) ## one-stage cluster sample dclus1<-svydesign(id=~dnum, weights=~pw,

Hello R users,  I am trying to obtain a direct adjusted survival curve. I am sending my whole code (see below). It's basically the larynx cancer data with Stage 1-4. I am using the cox model using coxph option, see the fit3 coxph. When I use the avg.surv option on fit3, I get the following error: "fits<-avg.surv(fit3, var.name="stage.fac", var.values=c(1,2,3,4), data=larynx)

Dear R-Users, I've recently used relsurv package for relative survival analysis. In particular I've tried to reproduce the examples proposed in the R-documentation about rsadd, rsmul and rstrans functions in R latest version (R 2.14.1). These examples don't run and the error message is always the following: data(slopop) data(rdata)

Hi, I would like to compare the hazard functions of two samples using the Cox proportional hazards model. For sample 1 I have individual time-to- event data. For sample 2 I don't have individual data, but grouped data that allows to obtain a hazard function. I am wondering if there is an R function that allows to obtain a hazard ratio of the two hazard funtions (under the