similar to: Strange error message

I am unable to get the basehaz function to apply a proportional hazards model to a new data frame. I replicated my specific situation with the example for coxph in the help, where I changed the x value of the first record from 0 to 1. Is there something incorrect in the syntax that I am using? Thanks in advance! test1 <- list(time= c(4, 3,1,1,2,2,3), status=c(1,NA,1,0,1,1,0),

Hello, When I try to to obtain the expected risk for a new dataset using coxph in the survival package I get an error. Using the example from ?coxph: > test1 <- list(time= c(4, 3,1,1,2,2,3),+ status=c(1,NA,1,0,1,1,0),+ x= c(0, 2,1,1,1,0,0),+ sex= c(0, 0,0,0,1,1,1))> cox<-coxph( Surv(time, status) ~ x + strata(sex), test1)

I stumbled onto this working on an update to coxph. The last 6 lines below are the question, the rest create a test data set. tmt585% R R version 2.12.2 (2011-02-25) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-unknown-linux-gnu (64-bit) # Lines of code from survival/tests/singtest.R > library(survival) Loading required package: splines

Dear all, I'm having difficulty getting access to data generated by survfit and print.survfit when they are using with a Cox model (survfit.coxph). I would like to programmatically access the median survival time for each strata together with the 95% confidence interval. I can get it on screen, but can't get to it algorithmically. I found myself examining the source of print.survfit to

I hope one and all will allow a stats question: When running a cox proportional hazards model ,there are two ways to deal with age, including age as a covariate, or to include age as part of the follow-up time, viz, Age as a covariate: tetest1 <- list(time= c(4, 3,1,1,2,2,3), status=c(1,NA,1,0,1,1,0), age= c(0, 2,1,1,1,0,0),

Hello, in the new Relase (1.4) i get a different (worser) result for read.table with as.is=T: it crash! Input file (t.txt, with a name, 5 character and a numeric column) Name short kind logable use save lag m "mo" "x" "n" "1" "n" 0 Ptp "PT" "l" "y" "m" "n" 0 R-Code

Hello all, (Thank for your reply) I have a web-application in Apache Tomcat, when i start R in this application, I used packe RSJava Code ROmegahatInterpreter interp; String [] rargs = {"--no-save"}; REvaluator e; interp = new ROmegahatInterpreter ( ROmegahatInterpreter.fixArgs(rargs),false ); e =new REvaluator (); Errors ================ R version 2.10.1 (2009-12-14)

Hi all, I just failed in loading a saved wordspace (13MB of size), and received these errors: Warning: stack imbalance in 'missing', 52 then 51 Warning: stack imbalance in 'if', 50 then 53 Warning: stack imbalance in 'as.environment', 57 then 59 Warning: stack imbalance in 'ls', 54 then 53 Warning: stack imbalance in '.Internal', 54 then 53 Warning: stack

With today's R 2.10.0(devel) I get: > anyDuplicated(c(1,NA,3,NA,5), incomp=NA) # expect 0 Warning: stack imbalance in 'anyDuplicated', 20 then 21 Warning: stack imbalance in '.Internal', 19 then 20 Warning: stack imbalance in '{', 17 then 18 [1] 0 > anyDuplicated(c(1,NA,3,NA,3), incomp=NA) # expect 5 Warning: stack imbalance in 'anyDuplicated', 20 then 21

Hi R users, I am using RMySQL to connect to a database in MySQL. I have 3 questions. 1)When I give the following command dbListTables(con) I get the output stack imbalance in .Call, 142 then 143 stack imbalance in <-, 140 then 141 stack imbalance in {, 138 then 139 stack imbalance in standardGeneric, 126 then 127 stack imbalance in class, 121 then 122 stack imbalance in

Full_Name: Antonio Possolo Version: 1.4.0 OS: Linux Submission from: (NULL) (24.25.141.205) ## inputFile has the following three lines (each without the initial ``## '') ## a,b ## m,1 ## n,3 ## and resides in $HOME/R fileHOME <- paste(Sys.getenv("HOME"), "/R/", sep="") fileNAME <- "inputFile" ## Given the command, z <-

Hello... I just installed R version 1.4.0 on my laptop running Redhat Linux 7.1. I downloaded the RPM from CRAN and when I try to use a function I have used on other Redhat systems, I get the following error message. -------- > library(qtl) > gastritis <- read.cross(format="csv",dir="/home/sen/qtl/data/gastritis", +

Hello R-sig-debian and (hopefully) Dirk: On Debian wheezy, I have the R packaging that CRAN (you) provide. I run into a little trouble while trying to fiddle with alternative BLAS. I know you and I went around on this last year and I think perhaps I've found something wrong in the framework, or I've just done something wrong. I installed the packages openblas-base and openblas-dev, and

Dear R-Helpers: I have tried everything I can think of and hope not to appear too foolish when my error is pointed out to me. I have some real data (18 points) that look linear on a log-log plot so I used them for a comparison of lm() and survreg. There are no suspensions. survreg.df <- data.frame(Cycles=c(2009000, 577000, 145000, 376000, 37000, 979000, 17420000, 71065000, 46397000,

Full_Name: Don Sun Version: 1.4.0 OS: Red Hat Linux release 6.2 Submission from: (NULL) (204.178.20.14) > type.convert(letters[1:2],as.is=T) stack imbalance in internal type.convert, 7 then 6stack imbalance in .Internal, 6 then 5 [1] "a" "b" Error: unprotect(): stack imbalance > version _ platform i686-pc-linux-gnu arch i686 os

I'm not sure if this has much significance or not -- but it sounds rather ominous. It doesn't appear to be new as it happens with 2.0.0 in Linux (but the formatting of the warning messages has improved). > contour(array(3e10, c(10,10), list(1:10, 11:20))) Warning: stack imbalance in 'contour', 20 then 24 Warning: stack imbalance in '.Internal', 19 then 23 Warning:

Dear R-user: I am using survreg(Surv()) for fitting a Tobit model of left-censored longitudinal data. For logarithmic transformation of y data, I am trying use survreg.distributions in the following way: tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist="gaussian", data=y.data, scale=0, weights=w) my.gaussian<-survreg.distributions$gaussian

1. The weibull is the only distribution that can be written in both a proportional hazazrds for and an accelerated failure time form. Survreg uses the latter. In an ACF model, we model the time to failure. Positive coefficients are good (longer time to death). In a PH model, we model the death rate. Positive coefficients are bad (higher death rate). You are not the first to be confused

Hello, I'm quite new to R and want to make a Weibull-regression with the survival package. I know how to build my "Surv"-object and how to make a standard-weibull regression with "survreg". However, I want to fit a translated or 3-parametric weibull dist to account for a failure-free time. I think I would need a new object in survreg.distributions, but I don't know how

Hey all, I am trying to use the survreg function in R to estimate the mean and standard deviation to come up with the MLE of alpha and lambda for the weibull distribution. I am doing the following: times<-c(10,13,18,19,23,30,36,38,54,56,59,75,93,97,104,107,107,107) censor<-c(1,0,0,1,0,1,1,0,0,0,1,1,1,1,0,1,0,0) survreg(Surv(times,censor),dist='weibull') and I get the following