similar to: Surv object in data.frame and Design package

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, Trying to combine two data frames with identical structure by rbind() or merge() I cannot find a way to preserve the class of a Surv object (see example). Reading the help page for rbind, I an uncertain if I could expect that a Surf oject retains it's class, but I would wish it did. Thanks Heinz T?chler R version 2.4.0 Patched (2006-11-03 r39792) Windows XP library(survival) ##

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 All, since years I am struggling with Surv objects in data.frames. The following seems to have to do with it. See below the modified example from the help page of survSplit. The original works, as expected. If, however, a Surv object is added to the data.frame, each record gets doubled. Is there some solution other than avoiding Surv objects in data.frames? Thanks, Heinz

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

Does Surv in psm handle interval2 data? The argument list seems to indicate it does but I get an error. Thanks, Chris # code library('survival') left <- c(1, 3, 5, NA) right <-c(2, 3, NA, 4) Surv(left, right, type='interval2') survreg(Surv(left, right, type='interval2') ~ 1) library('rms') Surv(left, right, type='interval2') # error args(Surv)

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

Hi Dear R-users I have a database with 18000 observations and 20 variables. I am running cox regression on five variables and trying to use survfit to plot the survival based on a specific variable without success. Lets say I have the following coxph: >library(survival) >fit <- coxph(Surv(futime, fustat) ~ age + rx, data = ovarian) >fit what I am trying to do is plot a survival

Full_Name: Victor Moreno Version: 2.2.0 OS: windows Submission from: (NULL) (213.151.99.160) summary of an object class Surv (package survival) hangs and closes R 2.2.0 I would like to have Surv objects in a data frame to build models easier: t<-rexp(100) s<-rbinom(100,1,.3) surv<-Surv(t,s) x1<-rnorm(100,10,2) x2<-rnorm(100,10,2) dat<-data.frame(surv,x1,x2)

I am writing to get a better handle on a warning I am getting from a coxph analysis I am doing. I am analysing age of onset of dementia *after* the onset of parkinson disease. My data looks like: age.park age.dem age.death censor x1 x2 x3 x4 1 76 87 88 0 16 33 E3 E3 2 75 84 84 0 33 36 E3 E3 3 77 81 81 1 NA NA

Dear Prof. Therneau I was impressed to discover that the 'survConcordance' now handles Surv() objects in counting format (example below to clarify what I mean). This is not documented in the help page for the function. I am very curious to see how a c-index is estimated in this case, using just the linear predictors. It was my impression that with left truncation the ordering of

Dear All, trying to write a data.frame, containing Surv objects to a csv-file I get "Error in dimnames(X) <- list(dn[[1L]], unlist(collabs, use.names = FALSE)) : length of 'dimnames' [2] not equal to array extent". See example below. May be, I overlooked something, but I expected that also data.frames containing Surv objects may be written to csv files. Is there a

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. >

Dear R-help - Thanks to those who replied yesterday (Christos H. and Thomas L.) regarding my question on coxph and model formula, the answers worked perfectly. My new question involves the following. I want to run several coxph models (package survival) with the same dataset, but different subsets of that dataset. I have found a way to do this, described below in functions subwrap1 and

Dear R People: I used the "Surv" function to produce the following object: >a <- Surv(1:4,2:5,c(0,1,1,0)) a [1] (1,2+] (2,3 ] (3,4 ] (4,5+] >str(a) Error in "[.Surv"(object, 1:ile) : subscript out of bounds > Why does str(a) give an error, please? Or did I do something wrong? Thanks in advance. R Version 1.9.1 Windows Sincerely, Laura Holt mailto: lauraholt_983

Hi, I'm trying to do a simple survival analysis on some data, and I'm having the following problem (here's my code and the error message): out <- Surv(fup,event=status) Error in Surv(fup, event = status) : argument "time2" is missing, with no default >From reading the documentation, it seems that I should be able to simply write: Surv(time1, event) if my data is

1. A Surv object is a matrix with some extra attributes. The as.matrix.Surv function removes the extras but otherwise leaves it as is. 2. The last several versions of the survival library were accidentally missing the S3method('as.matrix', 'Surv') line from their NAMESPACE file. (Instead it's position is held by a duplicate of the line just above it in the NAMESPACE file,

Hello, I have srv <- Surv(sample(1:10), sample(0:1, 10, replace = TRUE)) srv [1] 1 10 2+ 8 6+ 7+ 3 5+ 4+ 9+ srv.char <- as.character(srv) srv.char [1] " 1 " "10 " " 2+" " 8 " " 6+" " 7+" " 3 " " 5+" " 4+" " 9+" Is there an inverse to as.character(srv). That is, I would

Dear R users: I tried to use val.surv to give an internal validation of survival prediction model. I used the sample sources. # Generate failure times from an exponential distribution set.seed(123) # so can reproduce results n <- 1000 age <- 50 + 12*rnorm(n) sex <- factor(sample(c('Male','Female'), n, rep=TRUE, prob=c(.6, .4))) cens <- 15*runif(n) h

 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