similar to: variance estimator for the cumulative incidence function

Hi everyone, My purpose is to read a .CEL file into R. The .CEL file was created from a .CAB by using DTT software found on Affymetrix website I read the .CEL file in R using ReadAffy as follows: > d2=ReadAffy(widget=T) and I complete the fields as required. It does not complain. For example I could find the description: > description(d2) Experimenter name: BB Laboratory: FFL Contact

Hi, To use cuminc() from cmprsk package, if a subject has 2 events (both the event of interest and the event of competing risk), should I create 2 observations for this subject in the dataset, one for each event with different fstatus (1 and 2), or just 1 observation with whatever event that happened first? My analysis objective is calculate cumulative incidence for the event of interest.

Dear R-community, I would like to plot the numbers at risk for the different causes of failure at specific timepoints below a cumulative incidence function plot (plot.cuminc-function, cmprsk-package). For a Kaplan-Meier plot I know this is possible with the n.risk-argument in the survplot-function (rms-package), but to my knowledge no such readily-available functions are available for competing

Hi, I am wondering if anyone can explain to me if cumulative incidence (CI) is just "1 minus kaplan-Meier survival"? Under what circumstance, you should use cumulative incidence vs KM survival? If the relationship is just CI = 1-survival, then what difference it makes to use one vs. the other? And in R how I can draw a cumulative incidence plot. I know I can make a Kaplan-Meier

Hello everyone, I am a very new user of R and I have a query about the cuminc function in the package cmprsk. In particular I would like to verify that I am interpreting the output correctly when we have a stratification variable. Hypothetical example: group : fair hair, dark hair fstatus: 1=Relapse, 2=TRM, 0=censored strata: sex (M or F) Our data would be split into: Fair, male,

Hello, I have a problem regarding calculation of Cumulative Incidence Function. The event of interest is failure of bone-marrow transplantation, which may occur due to relapse or death in remission. The data set that I have consists of- lifetime variable, two indicator variables-one for relapse and one for death in remission, and the other variables are donor type (having 3 categories), disease

Dear R-help list members, I am trying to create my own axes when plotting a cumulative incidence curve using the plot.cuminc function in the CMPRSK library. The default x-axis places tick marks and labels at 0, 20, 40, 60, and 80 (my data has an upper limit of 96), whereas I want them at my own specified locations. Here is my example code: library(cmprsk) attach(MYDATA) MYCUMINC <-

Hi All, I'm trying to figure out the cumulative incidence curve in R in some limited time. I found in package "cmprsk", the command "plot.cuminc" can get this curve. But I noticed that there is no mark for the censored time there, comparing with the KM curve by "plot.survfit". Here are my codes (attached is the data): ----------------

Dear R users, I d like to assess the effect of "treatment" covariate on a disease relapse risk with the package cmprsk. However, the effect of this covariate on survival is time-dependent (assessed with cox.zph): no significant effect during the first year of follow-up, then after 1 year a favorable effect is observed on survival (step function might be the correct way to say that ?).

------------------------------ On Sat, May 16, 2015 8:04 AM BST Uwe Ligges wrote: >Not sure why this goes to R-devel. You just could have asked the >maintainer. Terry Therneau is aware of it and promised he will fix it. > The quickest fix is to add cmprsk to the recommended list , and that's is an R-devel issue. >On 16.05.2015 07:22, Hin-Tak Leung wrote: >> 'make

Hi all I do not understand why I am getting the following error message. Can anybody help me with this? Thanks in advance. install.packages("cmprsk") library(cmprsk) result1 <-crr(ftime, fstatus, cov1, failcode=1, cencode=0 ) one.pout1 = predict(result1,cov1,X=cbind(1,one.z1,one.z2)) predict.crr(result1,cov1,X=cbind(1,one.z1,one.z2)) Error: could not find function

'make check-all' for current R has been showing this error in the middle for a few months now - any thought on fixing this? I think cmprsk should be either included in the recommended bundle, or the survival vignette to not depend on it. Having 'make check-all' showing glaring ERROR's for a few months seems to defeat the purpose of doing any checking at all via 'make

Hi, I am computing the Nelson-Aalen (NA) estimate of baseline cumulative hazard in two different ways using the "survival" package. I am expecting that they should be identical. However, they are not. Their difference is a monotonically increasing with time. This difference is probably not large to make any impact in the application, but is annoyingly non-trivial for me to just

Dear all, I was wondering if anyone can help? I am an R user but recently I have resorted to SAS to calculate the probability of the event (and the associated confidence interval) for the Cox model with combinations of risk factors. For example, suppose I have a Cox model with two binary variables, one for gender and one for treatment, I wish to calculate the probability of survival for the

Dear Prof Gray and everyone, As our package developers discussed about incompatibility between Design and survival packages, I faced another problem with cmprsk- a survival dependent packacge. The problem is exactly similar to what happened to the Design package that when I just started running cuminc function, R was suddenly closed. These incidents suggest that maybe many other survival

Dear R-users, I am checking the proportional hazard assumption of a cox model for a given covariate, let say Z1, after adjusting for other relavent covariates in the model. To this end, I fitted cox model stratified on the discrete values of Z1 and try to get beslow estimator for the baseline cumulative hazard function (H(t)) in each stratum. As far as i know, if the proportionality assumption

R-users & helpers: I am using Amelia, mitools and cmprsk to fit cumulative incidence curves to multiply imputed datasets. The error message that I get "Error in eval(expr, envir, enclos) : invalid 'envir' argument" occurs when I try to fit models to the 50 imputed datasets using the "with.imputationList" function of mitools. The problem seems to occur

Dear R-users Has anybody implemented a function/package that will compute an individual's risk of an event in the presence of competing risks, adjusted for the individual's covariates? The only thing that seems to come close is the cuminc function from cmprsk package, but I would like to adjust for more than one covariate (it allows you to stratify by a single grouping vector). Any

Hi, I want to write own R functions for cumulative incidence function and also for the pseudovalue of the cumulative incidence function. Can you help me? Tas. [[alternative HTML version deleted]]

I installed the RApril with all the warnings of a pre-beta version, but had it quickly produce some beautiful graphs etc. Then, since I'm interested in regression, I downloaded the S-plus package for Aalen's additive regression model, and I got a fixed version for Windows/R already by the next day, but when I tried library(addreg) I got the error below. Error in system(call, intern) :