Displaying 20 results from an estimated 400 matches similar to: "unexpected GAM result - at least for me!"
2007 Dec 27
1
Lda and Qda
Hi all,
I'm working with some data: 54 variables and a column of classes, each observation as one of a possible seven different classes:
> var.can3<-lda(x=dados[,c(1:28,30:54)],grouping=dados[,55],CV=TRUE)
Warning message:
In lda.default(x, grouping, ...) : variables are collinear
> summary(var.can3)
Length Class Mode
class 30000 factor numeric ### why?? I
2008 Mar 27
1
dreaded p-val for d^2 of a glm / gam
OK,
I really dread to ask that .... much more that I know some discussion about p-values and if they are relevant for regressions were already on the list. I know to get p-val of regression coefficients - this is not a problem. But unfortunately one editor of a journal where i would like to publish some results insists in giving p-values for the squared deviance i get out from different glm and
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)
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
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 =
2009 May 26
3
split strings
Hi everybody,
I have a vector of characters and i would like to extract certain parts. My vector is named metr_list:
[1] "F:/Naval_Live_Oaks/2005/data//BE.tif"
[2] "F:/Naval_Live_Oaks/2005/data//CH.tif"
[3] "F:/Naval_Live_Oaks/2005/data//CRR.tif"
[4] "F:/Naval_Live_Oaks/2005/data//HOME.tif"
And i would like to extract BE, CH, CRR, and HOME in a
2009 May 26
3
split strings
Hi everybody,
I have a vector of characters and i would like to extract certain parts. My vector is named metr_list:
[1] "F:/Naval_Live_Oaks/2005/data//BE.tif"
[2] "F:/Naval_Live_Oaks/2005/data//CH.tif"
[3] "F:/Naval_Live_Oaks/2005/data//CRR.tif"
[4] "F:/Naval_Live_Oaks/2005/data//HOME.tif"
And i would like to extract BE, CH, CRR, and HOME in a
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
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
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 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 ?).
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
2018 Mar 23
1
restricted cubic spline in FGR function
Dear Thomas,
I want to use evaluate effect of Age using restricted cubic form in the FGR function as
Fgr.crr <- FGR(Hist(time, event) ~ rcs(Age_years), data=dat)
It provides error. " Error in parse(text = termtext, keep.source = FALSE): .... 1: response ~ rcs(Age_years
Do I need to change any of the R code?
Regards
Amalraj Raja
The University of Aberdeen is a charity
2011 Jun 24
1
Competing-risks nomogram
Hi R users,
I'd like to draw a nomogram using a competing-risks regression (crr function
in R), rather than a cox regression. However, the nomogram function provided
in the Design package is not good for this purpose.
Do you have any suggestion.
I really appreciate your help
Many thanks
F.Abdollah, MD
San-Raffele hospital
Milan, Italy
--
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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 Jan 02
0
Plot of Fine and Gray model
Dear all,
Happy New year!
I have used the 'crr' function to fit the 'proportional subdistribution
hazards' regression model described in Fine and Gray (1999).
dat1 is a three column dataset where:
- ccr is the time to event variable
- Crcens is an indicator variable equal to 0 if the event was achieved, 1
if the event wasn't acheived due to death or 2 if the event wasn't
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
2001 Nov 23
1
Changing strip widths in lattice plots
Hello R users,
I'm using xyplot (lattice) to plot some data. Unfortunately, the text that goes
into each strip is often too big to fit. For instance, one of the factors may
be labelled "Satisfaction with waiting time" which is too wide to fit. If I use
split.string() to wrap it onto two lines it is then too high to fit in the
strip. I'd prefer to apply split.string on the
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
2013 Mar 27
1
Crrstep help
Hi,
I'm using crrstep package to do stepwise covariate selection for the Fine &
Gray competing risks regression model. However, I keep getting an error
(please see below). Please help!!
> PHstep <-
crrstep(years~1+var1+var2+var3+var4+var5,scope.min=~1,censorcmprsk,
data=crisk, direction=c("forward"), crr.object = FALSE, trace = TRUE, steps
= 100)
crrstep(formula = years