similar to: penalized cox regression

Dear All, We are happy to announce, after a long gestation, the release of the new version of FRAILTYPACK (version 2.2-9.5) which is now available from CRAN. The package fit general frailty models using penalized likelihood estimation, for clustered or recurrent events. For instance : -- ADDITIVE FRAILTY MODELS for proportional hazards models with two correlated random effects (intercept

Dear All, We are happy to announce, after a long gestation, the release of the new version of FRAILTYPACK (version 2.2-9.5) which is now available from CRAN. The package fit general frailty models using penalized likelihood estimation, for clustered or recurrent events. For instance : -- ADDITIVE FRAILTY MODELS for proportional hazards models with two correlated random effects (intercept

Dear List, In documents (Therneau, 2003 : On mixed-effect cox models, ...), as far as I came to know, coxme penalize the partial likelihood (Ripatti, Palmgren, 2000) where as frailtyPenal (in frailtypack package) uses the penalized the full likelihood approach (Rondeau et al, 2003). How, then, coxme and coxph(...frailty(id, dist='gauss')) differs? Just the coding algorithm, or in

Dear R-listers, I have a very strange problem. I made a package (under Windows and Linux). The package passed the R CMD Check without problem. Then, I installed the package and executed a function which calls to a 'dll' mod<-frailtyPenal(Surv(time,status)~sex+age+cluster(id), + n.knots=8,kappa1=10000,data=kidney) mod Call: frailtyPenal(formula = Surv(time, status)

Hello, I was hoping that someone could answer a few questions for me (the background is given below): 1) Can the coxph accept an interaction between a covariate and a frailty term 2) If so, is it possible to a) test the model in which the covariate and the frailty appear as main terms using the penalized likelihood (for gaussian/t frailties) b)augment model 1) by stratifying on the variable that

Hi, when i run the following code i get this massege: "The instruction at 0x######## reference memory at 0x#######, the memory cannot be "read". and then i have to close R. what is the problem and how can i solve it? thanks in advance Avi my code # frailtypack library(frailtypack) cgd.ag <- read.csv("C:/rfiles/RE/cgd.csv") cgd.nfm <-frailtyPenal(Surv(TStart,

>Hello, I am hoping for assistance in regards to examining the contribution of stratified variables in a cox regression. A previous post by Terry Therneau noted that "That is the point of a strata; you are declaring a variable to NOT be proportional hazards, and thus there is no single "hazard ratio" that describes it". Given this purpose of stratification, in the

dear R-helper, I tried to find out a package in which i can have penalized maximum likelihood estimator applying on generalized extreme value distribution with beta function) but could not. would you please help me to know the name of the package. thanks for your help. S.Murshed --- r-help-request at stat.math.ethz.ch wrote: > Send R-help mailing list submissions to > r-help at

Dear, I want to analyze two-level survival data using a shared frailty model, for which I want to use the R package 'Frailtypack", proposed by Rondeau et al. The dataset was built using SAS software. I also tried to change the format using SPSS and Excell. My (reduced) dataset has following column names: ID entry time status family var1 I used following command: >

Dear R users, We are pleased to tell you that "FRAILTYPACK" has been updated. "FRAILTYPACK" stands now for general frailty models estimated with a semi-parametrical penalized likelihood, but also with a parametrical approach. In case of comments/corrections/remarks/suggestions -- which are very welcome --please contact the maintainer directly. Kind regards, The

Dear R users, We are pleased to tell you that "FRAILTYPACK" has been updated. "FRAILTYPACK" stands now for general frailty models estimated with a semi-parametrical penalized likelihood, but also with a parametrical approach. In case of comments/corrections/remarks/suggestions -- which are very welcome --please contact the maintainer directly. Kind regards, The

This is a follow-up to a query that was posted regarding some problems that emerge when running anova analyses for cox models, posted by Mathias Gondan: Matthias Gondan wrote: >* Dear List,*>**>* I have tried a stratified Cox Regression, it is working fine, except for*>* the "Anova"-Tests:*>**>* Here the commands (should work out of the box):*>**>*

Dear List, I have tried a stratified Cox Regression, it is working fine, except for the "Anova"-Tests: Here the commands (should work out of the box): library(survival) d = colon[colon$etype==2, ] m = coxph(Surv(time, status) ~ strata(sex) + rx, data=d) summary(m) # Printout ok anova(m, test='Chisq') This is the output of the anova command: > Analysis of Deviance Table

Hi everyone I am attempting to estimate a model with a frailty effect distributed as a lognormal variable.I am using the following code: frailtyPenal(formula, data, ..., RandDist = "LogN") I get the following error message: Error in frailtyPenal(Surv(,) ~ + , : unused argument(s) (RandDist = "") What can I do? Thanks for the help [[alternative HTML version deleted]]

Good afternoon, I am currently trying to do some work on survival analysis. - I hope to seek your advice re: 2 questions (1 general and 1 specific) (1) I'm trying to do a stratified Cox analysis and subsequently plot(survfit(object)). It seems to work for some strata, but not for others. I have tumor grade, which is a range of 1 - 4. When I divide this range of 1:4 into 2 groups, it

Hi all, I wish to do build discrete choice model to analyse habitat selection of wolverines. This can be done with a 'tricked' stratified Cox proportional hazard model. For each individual animal each selected position, and possible alternative non-used available positions are combined into strata. This means that one stratum contains a set of 1 used position and several positions which

Thanks for the reproducable example. I can confirm that it fails on my machine using survival 2-37.5, the next soon-to-be-released version, The issue is with NextMethod, and my assumption that the called routine inherited everything from the parent, including the environment chain. A simple test this AM showed me that the assumption is false. It might have been true for Splus. Working this

Dear R users: Recently, I learn to use penalized logistic regression. Two packages (penalized and glmnet) have the function of lasso. So I write these code. However, I got different results of coef. Can someone kindly explain. # lasso using penalized library(penalized) pena.fit2<-penalized(HRLNM,penalized=~CN+NoSus,lambda1=1,model="logistic",standardize=TRUE) pena.fit2

It seems that there is a problem in displaying subtitle in general, independently from multi-plot display. when I do plot (c(1,2,3), c(9,8,7), type = "l") title(main = "Main title", sub ="Sub title",cex.main=2, cex.sub = 2) subtitle doesn't get displayed > --- On Sat, 11/21/09, David Winsemius <dwinsemius at comcast.net> > wrote: >

Users are often surprised and alarmed that the summary of a linear mixed model fit by lmer provides estimates of the fixed-effects parameters, standard errors for these parameters and a t-ratio but no p-values. Similarly the output from anova applied to a single lmer model provides the sequential sums of squares for the terms in the fixed-effects specification and the corresponding numerator