similar to: How to join data.frames containing Surv objects?

Dear All, a Surv object I put in a data frame behaves somehow unexpected (see example). If I do a Cox regression on the original Surv object it works. If I put it in a data.frame and do the regression on the data frame it does not work. Seemingly it has to do with the class attribute, because if I change the class attribute to let "Surv" appeare first, again it works. Is this known?

Dear All, there seems to be some strange influence of the Design package on data.frame. If I build a data.frame containing a Surv object without loading the package Design, the data frame is usable to coxph. If instead I just load Design and build a data.frame afterwards, the naming of the Surv object is different and it does not work with coxph. (In my real application I loaded Design to use the

Hello All, ? Am replicating in R an analysis I did earlier using SAS. See this as a test of whether I'm ready to start using R in my day-to-day work. ? Just finished replicating a Kaplan Meier analysis. Everything seems to work out fine except for one thing. The 95% CI around my estimate for the median is substantially larger in R than in SAS. For example, in SAS I have a median of 3.29 with a

Dear R-helpers: I am trying to fit a multivariate Cox proportional hazards model, modelling survival outcome as a function of treatment and receptor status. The data look like below: # structure of the data str(sample.data) List of 4 $ survobj : Surv [1:129, 1:2] 0.8925+ 1.8836+ 2.1191+ 5.3744+ 1.6099+ 5.2567 0.2081+ 0.2108+ 0.2683+ 0.4873+ ... ..- attr(*, "dimnames")=List of 2

Dear R-helpers: I am trying to fit a multivariate Cox proportional hazards model, modelling survival outcome as a function of treatment and receptor status. The data look like below: # structure of the data str(sample.data) List of 4 $ survobj : Surv [1:129, 1:2] 0.8925+ 1.8836+ 2.1191+ 5.3744+ 1.6099+ 5.2567 0.2081+ 0.2108+ 0.2683+ 0.4873+ ... ..- attr(*, "dimnames")=List of 2

Regards! During the use of areski a2billing software I'm getting same problem all the time. Actually, after 15 minutes of speaking to someone over calling card, connection brakes. Installation was as smooth as it could be so I don't think I made same kind of a mess in that domain. This is the only problem in the aplication. In the logs everything seems to be fine. I'am sending You

Dear all, I need to do the same procedure on several files. But I don't know how to refer to the file name. Here is an example of what I am trying to do. List of files: file1(A,B,C, D1...Dn), file2(A,B,C,E1,...,En), file3(A,B,C,F1,...,Fn) Procedure I want to apply on each file: dft <- melt(df,id=c('A','B','C')) dft$X <- substr(dft$variable,1,3) dft$Y <-

Regards! During the use of areski a2billing software I'm getting same problem all the time. Actually, after 15 minutes of speaking to someone over calling card, connection brakes. Installation was as smooth as it could be so I don't think I made same kind of a mess in that domain. This is the only problem in the aplication. In the logs everything seems to be fine. I'am sending You

Am I correct in assuming that the output below essentially translates to "Males have a mean time that is significantly lower than Females"? Is this the correct way to interpret the fact that the coefficient is negative? Assume the variale sex is treated as a factor with Female =0 and Male=1. survmodel<-survreg(survobj~sex,data=data1, dist="weibull")

Hello: I am new to R Help so hopefully I will have included enough information to allow for valuable feedback on an error message I am receiving. I am trying to a fit a mixed effects cox model to binary elk telemetry data to look at movement decisions relative to other possibilities (specifically selection or avoidance of risk <- kauf_avg ) in a matched-case-control framework. >

Hello everybody! I'am just leaning Python and wanted to write something useful for me, an recursive masstagger for ogg-vorbis files. My script uses pyvorbis 1.3 from the Debian testing tree. so far here is my Problem: The pyvorbis bindings aren't documented. As i understand the pyvorbis package, this is a simpe 1:1 mapping to libvorbis. dir(pyvorbins-oject) gives me an refernece to an

I'm using R 1.7.0 on Windows 2000. I'm a long-time user of R, but am experiencing frustration because I can't figure out how to view the function definition of a non-exported method. (I know I can go view the source code or the code in the library directory but I am trying to view the function inside the R environment. In particular, library(mva) biplot.princomp Error: Oject

On 27/07/07, Gabriel McArthur <madeonamac at gmail.com> wrote: > I offered to do the web site a couple of weeks ago. Life got in the > way temporarily, and it took me a long time to make it look the way > that I wanted and to make it look the same in IE6. Anyway, I wanted > to get some feedback on what I had done. Very nice and clean. A few comments: 1) The header looks like

Dears, I have a question about copying reference objects using the initialize method. 1) If the latter has no arguments, there is no problem to copy an object. myClass = setRefClass("myClass", fields = list(value = "numeric") ) myClass$methods(initialize = function(...){ ? value <<- 1 ? callSuper(...) }) newObject = myClass$new() newObject$value = 2 copyObject =

Dear Colleagues: I would like to write a front end for a modeling function, but run into trouble when passing a weights argument. y <- 1:5 x <- c(1,3,2,5,4) w <- function(formula, ...) lm(formula, ...) lm(y ~ x, weights=c(1,1,1,2,2)) w(y ~ x) w(y ~ x, weights=c(1,1,1,2,2)) Error in eval(expr, envir, enclos) : ..1 used in an incorrect context, no ... to look in w <-

You've answered my question 2 about why the manual was in odd order > R CMD check was more of a check of the latex version of the files, not > the final manual. I was looking at the result of R CMD check, and it was in random order (perhaps file date?), not just a different collation choice. Very odd. I will cease worrying about what I might have "done wrong". I omitted the

Dear R users: I want to externally validate a model with val.surv. Can I use only calculated survival (at 1 year) and actual survival? Or I needed the survival function and actual survival. Thanks *Yao Zhu* *Department of Urology Fudan University Shanghai Cancer Center Shanghai, China* [[alternative HTML version deleted]]

 Dear R-users,   I  have two questions regarding validation and calibration of Survival regression models.   1.  I am trying to calibrate and validate a cox model using val.surv. here is my code:  f.1<-cph(Surv(time,event)~age, x=T, y=T, data=train)  test1<-test[,"age"]  val.surv(f.1, newdata=data.frame(test1), u=10)    but I get an error message:    Error in val.surv(f.1, newdata

Hi, I am analysing survival data (diagnosis time until death/cens) with time-dependent covariates. I would like to fit a cox model using the (start, stop] variable. In summary, I have the multiple internal time dependent covariates as follows; 1). LAS score (measured weekly on low risk patients, monthly on high risk) 2). EORTC score (measured monthly on low risk patients and every

Can anybody give me a neat example of interval censored data analysis codes in R? Given that suvreg(Surv(c(1,1,NA,3),c(2,NA,2,3),type="interval2")~1) works why does survreg(Surv(data[,1],data[,2],type="interval2")~1) not work where data is : T.1 T.2 Status 1 0.0000000 0.62873036 1 2 0.0000000 2.07039068 1 3 0.0000000