similar to: Survreg(), Surv() and interval-censored data

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)

Can survreg() handle interval-censored data like the documentation says? I ask because the command: survreg(Surv(start, stop, event) ~ 1, data = heart) fails with the error message Invalid survival type yet the documentation for Surv() states: "Presently, the only methods allowing interval censored data are the parametric models computed by 'survreg'"

Hi Everyone, This example code results in R 'crashing'; that is the R application closes with no warnings or error messages. #----------------------- myD <- read.table(stdin(), header=TRUE, nrows=20) Broth Salt pH Temp N Y Growth 1 310 9.0 2.92 10 90.0 NA 0 2 615 6.0 7.82 30 1.0 2 1 3 217 2.0 7.34 10 7.0 8

Hi all! I have two survival data sets looking at similar effects in different settings. One data set is only right censored, but the other is interval censored. In the right censored data set, there is an effect of one factor that causes very different shapes in survival curves (and non-proportional hazards) and I'd really like to say that the same factor has a similar effect in the other

Hello, ?When i generate data with the code below there appear NA as part of the generated data, i prefer to have zero (0) instead of NA on my data. Is there a command i can issue to replace the NA with zero (0) even if it is after generating the data?? Thank you library(survival) p1<-0.8;b<-1.5;rr<-1000 for(i in 1:rr){ r<-runif(45,min=0,max=1) t<-rweibull(45,p1,b)

Hi, I am trying to write a loop to recode my data from -999 to NA in R. What's the most efficient way to do this? Below is what I'm presently doing, which is inefficient. Thanks, Chris dat0 <- read.table("time1.dat") colnames(dat0) <- c("e1dq", "e1arcp", "e1dev", "s1prcp", "s1nrcp", "s1ints",

Better would be to use interval censored data. Create your data set so that you have (time1, time2) pairs, each of which describes the interval of time over which the tag was lost. So an animal first captured at time 10 sans tag would be (0,10); with tag at 5 and without at 20 would be (5,20), and last seen with tag at 30 would be (30, NA). Then survit(Surv(time1, time2,

The rms ("Regression Modeling Strategies") package has undergone a massive update. The entire list of updates is at the bottom of this note. CRAN has the update for linux and will soon have it for Windows and Mac - check http://cran.r-project.org/web/packages/rms/ for availability. This rms update relies on a major update of the Hmisc package. The most user-visible changes are:

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

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) ##

Hi, I'm trying to using pspline in bic.surv{BMA}. ############################# library(BMA) library(survival) data(veteran) test.bic.surv<- bic.surv(Surv(time,status) ~ karno+pspline(age,df=3)+diagtime+prior, data = veteran, factor.type = TRUE) summary(test.bic.surv, conditional=FALSE, digits=2) ############################# The results are:

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, I want to analyze two-level survival data using a shared frailty model, for which I want to use the R package 'Frailtypack", proposed by Rondeau et al. The dataset was built using SAS software. I also tried to change the format using SPSS and Excell. My (reduced) dataset has following column names: ID entry time status family var1 I used following command: >

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,

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)

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 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

Dear everyone, My question involves the use of the survival object. We can have Surv(time,time2,event, type=, origin = 0) (1) As detailed on p.65 of: http://cran.r-project.org/web/packages/survival/survival.pdf My data (used in my study) is 'right censored' i.e. my variable corresponding to 'event' indicates whether a person is alive (0) or dead (1) at date last seen