similar to: Plotting question re. cuminc

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 <-

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

Hello, I have a question regarding competing risk regression using cmprsk package (function crr()). I am using R2.9.1. How can I do to assess the effect of qualitative predictor (gg) with more than two categories (a,b,c) categorie c is the reference category. See above results, gg is considered like a ordered predictor ! Thank you for your help Jan > # simulated data to test > set.seed(10)

Hi, I would like to write a function which has the following syntax: myfn <- function(formula, ftime, fstatus, data) { # step 1: obtain terms in `formula' from dataframe `data' # step 2: obtain ftime from `data' # step 3: obtain fstatus from `data' # step 4: do model estimation # step 5: return results } The user would call this function as: myfn(formula=myform,

Hello everyone, These are some questions about the 'pec' function in R. These questions deal with prediction error curves and their derivation. Prediction error curves are documented in, for example, "Efron-type measures of prediction error for survival analysis" by Gerds and Schumacher. I have detailed some syntax that I have used at the bottom of this email. The associated

Dear R-help, I'm very sorry to ask 2 questions in a week. I am using the package 'crr' and it does exactly what I need it to when I use the dataset a. However, when I use dataset b I get the following error message: Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number =

Hi All, I am running a scatter plot and trying to add a best fit line. I use an abline function, but get no line drawn over the points. I also get no error. I arm using V 2.10.0 on Windows 7. Here is my code, including the SAS transport file import: require (foreign) require (chron) require (Hmisc) require (lattice) clin <- sasxport.get("y:\\temp\\subset.xpt") attach(clin)

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

Dear all, I am trying to use the crr function in the cmprsk package version 2.2 to analyse 198 observations.I have receive the error in solve.default. Can anyone give me some insights into where the problem is? Thanks here is my script : cov=cbind(x1,x2) z<-crr(ftime,fstatus,cov)) and data file: x1 x2 fstatus ftime 0 .02 1 263 0 .03 1 113 0 .03 1 523

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.

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 everyone, This is just a quick double check. It concerns the 'scatterplot function' in R. I have 6 curves and I wish to represent each of them by a different kind of line (their colour must be black). The curves are derived from the cuminc function...the coordinates of which are in 'xx'. Upon reading the documentation in R, it looks like I can use the 'on/off'

Hi, I am trying to figure out how to put tick marks for censored observations using plot.cuminc for my competing risk analysis (survfit does this automatically). I've searched online for resources but found nothing. Does anybody know how to do this? Thank you in advance for your input. KC [[alternative HTML version deleted]]

Dear friends: I'm interested to make a stacked plot of cumulative incidence. that's, the cuminc model is fitted [fit=cuminc(time, relapse)] and cumulative incidence is in place. I'd like to stack the cuminc plots (relapse of luekemia and death free from leukemia, for example) , then the constituent ratio of leukemia relapse and treatment related mortality is very clear. Can

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

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

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,

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): ----------------

I've developed an indexer which embeds a keyframe index track in Ogg files. It embeds the index in its own track, so that players that don't understand or don't want to use the index can just ignore it. Ogg needs this to make seeking over networks faster and more efficient. Currently we must do a bisection search when seeking, which usually takes aound 6 HTTP requests, give or

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