Displaying 20 results from an estimated 6000 matches similar to: "competing risk model with time dependent covariates"
2008 Aug 22
0
Re : Help on competing risk package cmprsk with time dependent covariate
Hello again,
I m trying to use timereg package as you suggested (R2.7.1 on XP Pro).
here is my script based on the example from timereg for a fine & gray model in which
relt = time to event, rels = status 0/1/2 2=competing, 1=event of interest, 0=censored
random = covariate I want to test
library(timereg)
rel<-read.csv("relapse2.csv", header = TRUE, sep = ",",
2008 Jul 27
0
competing risk model with time dependent covariates under R or Splus
This message was also sent to the MEDSTATS mailing list, so here is the reply I posted to that:
Philippe,
The machinery to use is to split follow-up time so finely that you can safely assume that rates are constant in each interval, and then just stuff it all into a Poisson model. This allows you to use any kind of time-dependent variables as well as accommodating competing risks.
In the Epi
2008 Aug 22
1
Help on competing risk package cmprsk with time dependent covariate
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 ?).
2008 Aug 20
0
cmprsk and a time dependent covariate in the model
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
2009 Feb 27
2
Competing risks adjusted for covariates
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
2007 May 25
0
Competing Risks Analysis
I am working on a competing risks problem, specifically an analysis of
cause-specific mortality. I am familiar with the cmprsk package and
have used it before to create cumulative incidence plots. I also came
across an old (1998) s-news post from Dr. Terry Therneau describing
a way to use coxph to model competing risks. I am re-producing the
post at the bottom of this message.
I would like to
2006 Aug 17
1
putting the mark for censored time on 1-KM curve or competing risk curve
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):
----------------
2009 Mar 25
2
Competing risks Kalbfleisch & Prentice method
Dear R users
I would like to calculate the Cumulative incidence for an event
adjusting for competing risks and adjusting for covariates. One way to
do this in R is to use the cmprsk package, function crr. This uses the
Fine & Gray regression model. However, a simpler and more classical
approach would be to implement the Kalbfleisch & Prentice method (1980,
p 169), where one fits cause
2013 Feb 05
1
Calculating Cumulative Incidence Function
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
2008 Dec 15
0
Cumulative Incidence : Gray's test
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,
2008 Dec 08
0
Query in Cuminc - stratification
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,
2011 Jul 20
0
Competing risk regression with CRR slow on large datasets?
Hi,
I posted this question on stats.stackexchange.com 3 days ago but the
answer didn't really address my question concerning the speed in
competing risk regression. I hope you don't mind me asking it in this
forum:
I?m doing a registry based study with almost 200 000 observations and
I want to perform a competing risk analysis. My problem is that the
crr() in the cmprsk package is
2012 Nov 28
0
Numbers at risk below cumulative incidence function plot (plot.cuminc, cmprsk-package)
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
2007 Jul 03
0
Statistics Question not R question: competing risks and non-informative censoring
All,
I am working with Emergency Department (ED) Length of Stay Data. The ED
visit can end in one of a variety of ways (Admit, discharge, transfer,
etc...) Initially, I have modeled the time to event by fitting a survival
model to the time the outcome of interest and treat all other outcomes as
censoring. However I recently came across the cmprsk package in R which
seems to be developed
2009 Aug 02
1
Competing Risks Regression with qualitative predictor with more than 2 categories
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)
2009 Feb 24
0
help: calculations for causespecific hazard ratios in a competing risks analysis with timedependent covariates
Dear R users:
Analysis of the impact of a time-dependent covariate (GVHD or use of steroid after bone marrow transplantation) on two competing endpoints (invasive fungal infection and death) is frequently encountered in the setting of BMT data. Coxph package can be used as the following:
for the analysis of GVHD:
> gvhd -> coxph(Surv(start,stop,status = =1) ~ GVHD, data=bmt.data)
2010 May 06
1
Understanding of survfit.formula output
Dear list,
I am not familiar with survival analysis and I would need your help to
understand a result I have obtained.
I have used the following command line to look at number of events and
probability of survival at the first 5 years:
> su = summary(survfit(Surv(a[, Date], a[, Event]) ~ strata(a[,Prediction]),
data = a), times=c(0,1,2,3,4,5))
I have studied two kind of events (disease-free
2013 Mar 07
1
Comparing Cox model with Competing Risk model
I have a competing risk data where a patient may die from either AIDS or
Cancer. I want to compare the cox model for each of the event of interest
with a competing risk model. In the competing risk model the cumulative
incidence function is used directly. I used the jackknife (pseudovalue) of
the cumulative incidence function for each cause (AIDS or Cancer) in a
generalized estimating equation. I
2009 Oct 27
1
Error in solve.default peforming Competing risk regression
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
2008 Mar 27
0
competing risks regression
Dear R users,
I used crr function in R package 'cmprsk' to fit a competing risks
model. There were no any error or
warning messages during running the function, but the output was obvious
not correct.
I saved the model fit as an object called f.crr. I extracted bfitj from
the object by doing f.crr$bfitj, and found
values of bfitj were extremely large (around 1e+138). I tried all