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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,

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 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 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

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]]

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

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 | Center/ID), data=cgd.ag) And a note to the poster-- you should

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)

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

Assume that we collect below data : - subjects = 20 males + 20 females, every single individual is independence, and difference events = 1, 2, 3... n covariates = 4 blood types A, B, AB, O http://r.789695.n4.nabble.com/file/n4245397/CodeCogsEqn.jpeg ?m = hazards rates for male ?n = hazards rates for female Wm = Wn x ?, frailty for males, where ? is the edge ratio of male compare to female Wn =

On Thu, 4 Aug 2016 at 17:53 Michael Sumner <mdsumner at gmail.com> wrote: > On Thu, 4 Aug 2016 at 11:17 Paul Murrell <paul at stat.auckland.ac.nz> wrote: > >> Hi >> >> Just to clarify, I think this IS a problem with grid.path() as well as >> polypath(). >> >> > Hi, oh dear - sorry about that > > I appreciate the deeper explanation, I

Hello, I've got a strange problem here: I installed Samba 3.0.2a using the official rpms on a SuSE 9.0 machine. I configured samba in the smb.conf as a PDC and created user and machine accounts on the system as well as in the smbpasswd. Afterwards I was able to join the domain with my Windows XP client. After a reboot I am unable to log on to the Domain on my WinXP client. There's just the

Hi Just to clarify, I think this IS a problem with grid.path() as well as polypath(). For the example you give, grid.path() diverts to drawing a polygon (because there is no 'id' specified), and the NAs in 'x' generate two separate polygons, which get drawn one on top of the other. The correct analogy to the polypath() example is ... x2 <- matrix(x[!is.na(x)], ncol=2)

Hi, I see different results in png() and pdf() for polypath() on Windows when using the "winding" rule ## overlapping, both clock-wise x <- cbind(c(.1, .1, .6, .6, NA, .4, .4, .9, .9), c(.1, .6, .6, .1, NA, .4, .9, .9, .4)) pfun <- function() { plot(x) polypath(x * 0.8 + 0.2, rule = "winding", col = "#BEBEBE80") polypath(x, rule =

Looks like the Geforce 7050 isn't yet supported in either the nv or nouveau drivers - or at least running them both fail miserably. I also pulled the latest drm and nouveau sources from git and compiled them - this setup gave more errors and appeared to make it further toward success, but still ended with the usual no screens found error. Would a Renouveau dump from my system be helpful? I

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

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 details see the corresponding NEWS files in the pkgs. We are