similar to: NEW release of FRAILTYPACK

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: >

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

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

Hello I would like to compare the results obtained with a classical non parametric proportionnal hazard model with a parametric proportionnal hazard model using a Weibull. How can we obtain the equivalence of the parameters using coxph(non parametric model) and survreg(parametric model) ? Thanks Virginie

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 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 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

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 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]]

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

Hi everybody, I'm trying to create a numerical data frame on which to perform PRCC. So far I have created a data frame that consists of function/vector output that displays in numerical form, but when I try and run PRCC (from epiR package) I get the following error message: "Error in solve.default(C) : Lapack routine dgesv: system is exactly singular" It appears this is because

Hi everyone, I emailed yesterday thinking I had a problem with reading matrix information as numerical output into epiR. After working on the data frame today, I realise it's a problem with the data itself rather than the syntax. An original data frame of min max T1 1.500000e+01 3.999954e+01 SE1 0.000000e+00 1.000000e+00 PRE

We're involved in a project that the requirements could be satisfied with both samba3 and 4. Anyway I am testing what can be done with Samba4 and after following the tutorial published in the official wiki, I was able to create my test domain, and join WinXP and Win7 machines to it without a problem. I still need to test the GPO functionality, and some other stuff, but before continuing with

R-Listers: I am doing a quasi-maximum likelihood estimation and I get a "subscript out of bound" error message, Typically I would think this means that a subscript used in the function is literally out of bounds however I don't think this is the case. All I change in the code is a constant, that is hard-wired in (not data dependent and not parameter dependent), furthermore,

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

https://bugzilla.samba.org/show_bug.cgi?id=5811 Summary: rsync error: error allocating core memory buffers (code 22) at io.c(635) Product: rsync Version: 3.0.4 Platform: x64 OS/Version: Linux Status: NEW Severity: blocker Priority: P3 Component: core AssignedTo: wayned@samba.org

  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

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 =

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]]