similar to: jointModel error messages

I contacted the package developer and that lead to me removing events at time 0 (or subjects with only 1 longitudinal measurement). I then still had the error message "Can't fit a Cox model with 0 failures" which I have managed to avoid by adding 1.8*10^(-15) to all my survival times, any number greater than this also works but nothing smaller! Any explanation of this would help!

Dear R-users, I'd like to announce the release of the new package JM (JM_0.1-0 available from CRAN) for the joint modelling of longitudinal and time-to-event data. The package has a single model-fitting function called jointModel(), which accepts as main arguments a linear mixed effects object fit returned by function lme() of package nlme, and a survival object fit returned by either

Dear R-users, I'd like to announce the release of the new package JM (JM_0.1-0 available from CRAN) for the joint modelling of longitudinal and time-to-event data. The package has a single model-fitting function called jointModel(), which accepts as main arguments a linear mixed effects object fit returned by function lme() of package nlme, and a survival object fit returned by either

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modeling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the survival outcome and we wish to account for the effect of a time-dependent covariate measured with error.

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modeling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the survival outcome and we wish to account for the effect of a time-dependent covariate measured with error.

Hi all: I am a user of "JM" package. Here's the problem of "sample size". The warning is: Error in jointModel(fitLME, fitSURV_death, timeVar = "time", method = "piecewise-PH-GH") : sample sizes in the longitudinal and event processes differ. According to the suggestion of "missing data",I use the same data set(data_JM) without any

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modeling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the survival outcome and we wish to account for the effect of an endogenous (aka internal) time-dependent

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modeling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the survival outcome and we wish to account for the effect of an endogenous (aka internal) time-dependent

Hello all: I am using exactaudio copy (EAC) with wine on linux (suse 10.1) So far I had no problems with drive recognition. Recently I've attached another drive to the IDE 0 slave port and this drive is not recognized by EAC/wine. Here is my 'cdrecord dev=ATA -scanbus' output: scsibus0: 0,0,0 0) * 0,1,0 1) 'TEAC ' 'CD-W512EB '

Hello, I am using the package gamlss in R to plot repeated measurements. The command I am using is par.plot(). It works great except one thing about the label of the axises. I tried to label both x and y axises using ylab and xlab options. But the plot only gives variable variables. The labels did not show up. Below is the code I used. Any comments are appreciated! Thanks. library(gamlss)

Hi, I have installed R (2.0.0) onto a two processor machine running Windows XP (these two processors have been split into 4 logical processors), with 4Gb of RAM. Rather than multi-threading, I wanted to run 2 instances of R on the machine in parallel, which uses two of the logical processors. Unfortunately, R seems to be accessing a total of 1Gb of RAM, not taking advantage of 2 lots of 1Gb.

Hello, I have some (possibly very simple) questions about subscriptions: I store my old mails in /home/oldmails/ in one Maildir where I have only read-only permissions (I cannot delete, create or modify any files). Under thunderbird, I can successfully log in and read my new mails, but I cannot subscribe (?) within thunderbird to oldmails (it is grey not black as other folders). What did I do

Hi Graham, I created a bug report with a reproducer for the failures I’ve got: https://bugs.llvm.org/show_bug.cgi?id=35288 I have also found that LTO reverts everything the partial inliner has done. Maybe the partial inliner should not be used at the first LTO phase (compilation). I hope I’ll have a chance to look at the code size regressions this week. Thanks, Evgeny Astigeevich From:

While trying to set up samba as a PDC, I followed O'Reillys Using Samba. This resulted in the following smb.conf: [global] workgroup = GRAHAM encrypt passwords = true log level = 1 max log size = 1000 hosts allow = 192.168.0/24 192.168.1/24 hosts deny = 1.1.1.1/0.0.0.0 domain logons = yes security = user os level = 34 local master = yes preferred master = yes domain master = yes [temp]

Hi Evgeny, I just realized that if these are compile-time errors I can help investigate on my end. Do you have something I can use to reproduce? Cheers, Graham Yiu LLVM Compiler Development IBM Toronto Software Lab Office: (905) 413-4077 C2-707/8200/Markham Email: gyiu at ca.ibm.com From: Graham Yiu/Toronto/IBM To: Evgeny Astigeevich <Evgeny.Astigeevich at arm.com> Cc:

Hi Graham, In that case I''ll have to redefine File.delete and Dir.rmdir in the win32-file package and win32-dir packages, respectively. Please add a feature request on the project page so I don''t forget. I should have it done this weekend. Dan Foster, Graham wrote: > I want to create a long UNC based path.. Server and top level will exist, > but subdirectories

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modelling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the time-to-event outcome and we wish to account for the effect of a time-dependent covariate measured with

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modelling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the time-to-event outcome and we wish to account for the effect of a time-dependent covariate measured with

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modelling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the time-to-event outcome and we wish to account for the effect of a time-dependent covariate measured with

Dear R-users, I'd like to announce the release of the new version of package JM (soon available from CRAN) for the joint modelling of longitudinal and time-to-event data using shared parameter models. These models are applicable in mainly two settings. First, when focus is in the time-to-event outcome and we wish to account for the effect of a time-dependent covariate measured with