search for: frailtypack

I can't comment on frailtypack issues, but would like to mention that coxme will handle nested models, contrary to the statement below that "frailtypack is perhaps the only .... for nested survival data". To reprise the original post's model cgd.nfm <- coxme(Surv(Tstart, Tstop, Status) ~ Treatment + (1 |...

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 dir...

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 dir...

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 random e...

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 random e...

A new version of the package FRAILTYPACK is now available on CRAN. -- possibility to fit now a Shared and a Joint Frailty model with a log-normal distribution for the random effects. -- possibility to deal with interval-censored data (for a shared frailty model) -- possibility to fit a joint frailty model for clustered data For more...

A new version of the package FRAILTYPACK is now available on CRAN. -- possibility to fit now a Shared and a Joint Frailty model with a log-normal distribution for the random effects. -- possibility to deal with interval-censored data (for a shared frailty model) -- possibility to fit a joint frailty model for clustered data For more...

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, TStop, Status)~cluster(Center)+subcluster(ID) Treatment,data=cgd.ag,Frailty=TRUE,n.knots=8,kappa1=50000, cross.validation=TRUE,recurrentAG=TRUE)...

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]]

  To   R group Help Desk     I am a user of R software.  I am facing a problem while using "frailtyPenal" command in R.2.11.1. When I use these command, R closes completely without any prior alert message. Can I know what would be the reason? My data size is 7050 records with atleast 25 variables.   Looking forward to hear from you.   Truely Kalaivani M.Kalaivani, M.Sc. Scientist-I

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 approach too? coxph(...frailty(id, dist='gamma')) estimates by means of the penalized likelihood appr...

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: > frailtyPenal(Surv(time, status) ~...

...male Wn = frailty for females X = covariates, blood types effects ? = coefficients of blood types I would like to apply frailty model to get below results:- 1) 1 edge ratio between male and female ? 2) 4 coefficient values of blood types ? Under this situation, shall I use which package (coxme or frailtypack)? will coxme function able to cope with it? -- View this message in context: http://r.789695.n4.nabble.com/Joint-modelling-of-survival-data-tp4245397p4245397.html Sent from the R help mailing list archive at Nabble.com.

Hi, What is the function to calculate penalized cox regression? frailtyPenal in frailtypack R package imposes max 2 strata. I want to use a function that reduces all my variables without stratifying them in advance. Look forward to your reply carol --------------------------------- [[alternative HTML version deleted]]

Dear R-help, I am trying to estimate a Cox model with nested effects, or better h(t,v,w)=v*w*h0(t)*exp(B'x) where h(t,v,w) is the individual hazard function w and v are both frailty terms (gamma or normal distributed) I have 12 clusters and for each one of them I would like to associate a realization of v, while w is a random effect for the whole population. At the population level

Hello, I have a cohort with approx 1,200 patients at the ages of 30-65 that had their first myocardial infarction during 1992: · They were in a follow up until 2005. · About 400 of them died during this period of time (right censored) · Each one of them had up to 4 mi recurrent events. I am using the semi-parametric model in order to assess the relationship of

...ackage). Updated packages ---------------- bnlearn (2.9), catspec (0.96), cda (1.1.3), clue (0.3-44), coin (1.0-21), crs (0.15-13), cvTools (0.3.0), Deducer (0.6-2), directlabels (2.4), doRNG (1.2.1), dplR (1.5.3), DSL (0.1-1), eqtl (1.1-7), ergm (3.0-1), ergm.userterms (3.0-1), fda.usc (0.9.6), frailtypack (2.2-22), games (1.0-5), gdsfmt (0.9.6), geosphere (1.2-27), GeoXp (1.5.6), GLDEX (1.0.4.3), gMCP (0.7-8), GSM (1.3), hive (0.1-14), HLMdiag (0.1.5), HumMeth27QCReport (1.2.13), ibr (1.4.1), LaplacesDemon (12.03.05), lattice (0.20-5), lattice (0.20-6), lifecontingencies (0.9.1), lifecontingencies (...

...ons(repos = "http://lib.stat.cmu.edu/R/CRAN/") options(repos = "http://cran.cnr.berkeley.edu/") #failPackages is the "black list". # Things that don't build cleanly with FC4, but I # hope it will build someday soon. failPackages <- c("deldir","frailtypack","fSeries","fCalendar","fExtremes","fPortfolio","hmm.discnp","knncat","labdsv","survrec", "SciViews","RGrace","uroot","fMultivar","fOptions","gcmrec",&quo...

...ons(repos = "http://lib.stat.cmu.edu/R/CRAN/") options(repos = "http://cran.cnr.berkeley.edu/") #failPackages is the "black list". # Things that don't build cleanly with FC4, but I # hope it will build someday soon. failPackages <- c("deldir","frailtypack","fSeries","fCalendar","fExtremes","fPortfolio","hmm.discnp","knncat","labdsv","survrec", "SciViews","RGrace","uroot","fMultivar","fOptions","gcmrec",&quo...

...t;,"FLCore","FLEDA","flexclust","flexmix","fMultivar","fOptions","foreign"," FortranCallsR","fortunes","forward") TEMP <- c(TEMP,"fpc","fPortfolio","fracdiff","frailtypack","fSeries","ftnonpar","FunCluster","fuzzyRankTests","g.data","gafit","gam","gamair","gamlss","gamlss.tr","GammaTest","gap","gbm","gclus","gcmrec&quot...