Displaying 20 results from an estimated 6000 matches similar to: "strata in crr (cmprsk library)"
2007 Jul 05
0
speed up crr function in cmprsk package
I am trying to use the crr function in the cmprsk package to analyze a large
patient dataset (45000 +), The model has 100 + covariates and 5 competing
risks. I am finding that R seems to get bogged down and even if I let it run
for several hours I don't get anything back. Am I expecting too much, or are
there ways to speed up the process? Any help is appreciated.
Best,
Spencer
2006 May 10
0
using crr in cmprsk
Hi,
I need to fit model using crr, however my covariate is
categorical with 3 levels. I use
crr(time,status,agesplit,failcode=1,cencode=0) where
agesplit is defined as <20,21-29,>30 years, so it
takes 0, 1 or 2 for each patient. I hoped to get
estimated coefficients for the levels 1 and 2 w.r.t
level 0 as in coxph. But, I didn't. Could someone
please help me to use crr in this
2013 Oct 18
1
crr question in library(cmprsk)
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
2015 Jun 15
2
Different behavior of model.matrix between R 3.2 and R3.1.1
Terry - your example didn't demonstrate the problem because the variable
that interacted with strata (zed) was not a factor variable.
But I had stated the problem incorrectly. It's not that there are too
many strata terms; there are too many non-strata terms when the variable
interacting with the stratification factor is a factor variable. Here
is a simple example, where I have
2015 Jun 15
2
Different behavior of model.matrix between R 3.2 and R3.1.1
Terry - your example didn't demonstrate the problem because the variable
that interacted with strata (zed) was not a factor variable.
But I had stated the problem incorrectly. It's not that there are too
many strata terms; there are too many non-strata terms when the variable
interacting with the stratification factor is a factor variable. Here
is a simple example, where I have
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 = ",",
2009 Jun 25
2
crr - computationally singular
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 =
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
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
2007 Feb 15
1
bootcov and cph error
Hi all,
I am trying to get bootstrap resampled estimates of covariates in a Cox
model using cph (Design library).
Using the following I get the error:
> ddist2.abr <- datadist(data2.abr)
> options(datadist='ddist2.abr')
> cph1.abr <- cph(Surv(strt3.abr,loc3.abr)~cov.a.abr+cov.b.abr,
data=data2.abr, x=T, y=T)
> boot.cph1 <- bootcov(cph1.abr, B=100, coef.reps=TRUE,
2015 May 16
1
That 'make check-all' problem with the survival package
'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
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)
2015 May 16
2
That 'make check-all' problem with the survival package
------------------------------
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
2015 Jun 16
1
Different behavior of model.matrix between R 3.2 and R3.1.1
Terry Therneau has been very helpful on r-help but we can't figure out
what change in R in the past months made extra columns appear in
model.matrix when the terms object is subsetted to remove stratification
factors in a Cox model. Terry has changed his logic in the survival
package to avoid this issue but he requires generating a larger design
matrix then dropping columns.
A simple
2011 Sep 05
1
SAS code in R
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
2011 Feb 21
2
Interpreting the example given by Prof Frank Harrell in {Design} validate.cph
Dear R-help,
I am having a problem with the interpretation of result from validate.cph in
the Design package.
My purpose is to fit a cox model and validate the Somer's Dxy. I used the
hypothetical data given in the help manual with modification to the cox
model fit. My research problem is very similar to this example.
This is the model without stratification:
> library(Design)
> f1
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
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
2004 Sep 09
2
Rd syntax error detected in CRAN daily checks
Please forgive me if you already received this. I had an e-mail sending
glitch this morning.
http://cran.r-project.org/src/contrib/checkSummary.html reported an
error in Design.trans.Rd
* checking Rd files ... ERROR
Rd files with syntax errors:
/var/mnt/hda3/R.check/r-devel/PKGS/Design/man/Design.trans.Rd:
unterminated section 'alias'
The .Rd file is attached. It begins