similar to: Correlation between random effects in the package coxme

Hi there, I have a question on fitting data by coxme. In particular I want to fit a random intercept and random slope cox model. Using the rats dataset as an example, I generated another covariate x2 and want to specify a random slope for x2. Here is my code: x2=matrix(rep(runif(50), 3), 50, 3) x2=as.vector(t(x2)) rats2=cbind(rats, x2) But when I used the coxme function as follows, it gave

Hi, R experts I am currently using lmekin() function in coxme package to fit a mixed effect model for family based genetic data. How can I extract the p value from a lmekin object? When I print the object in R console, I can see the p value and Z value are just over there. But I can not extract them by the coef() function. kinfit$coefficient$fixed (kinfit is the name of the lmekin object)

I've moved nlme from Depends to Imports in my coxme package. However, a few of the examples for lmekin use one of the data sets from nlme. This is on purpose, to show how the results are the same and how they differ. If I use data(nlme::ergoStool) the data is not found, data(nlme:::ergoStool) does no better. If I add importFrom(nlme, "ergoStool") the error message is that

I am making the question clear. Please help. > Dear R experts > > I was using kinship package to fit mixed model with kinship matrix. > The package looks like lme4, but I could find a way to extract p-value > out of it. I need to extract is as I need to analyse large number of > variables (> 10000). > > Please help me: > > require(kinship) > > #Generating

I'm having a problem rebuilding a package, new to me in R 2.15.0 (Linux) It hits all that contain the line \usepackage[pdftex]{graphics} and leads to the following when running R CMD check on the directory. (I do this often; a final run on the tar.gz file will happen before submission.) Since I float and resize my figures, removing the line is fatal in other ways.

Dear all, I have encountered the following problem where coxme seems to allow model with only random effect in R 2.11.1 but not in R 2.13.0. Following is the error message using rat example data. Any comment on this is appreciated. In R2.13 > library(coxme) > rat1 <- coxme(Surv(time, status) ~ rx + (1|litter), rats) > rat0 <- coxme(Surv(time, status) ~ (1|litter), rats)

Version 2.2 of coxme has been posted to CRAN, Windows versions and mirrors should appear in due course. This is a major update with three features of note: 1. A non-upwardly compatable change: Extractor functions: beta= fixed effects, b=random effects nlme lme4 coxme <2.2 coxme 2.2 lmekin 2.2 ------------------------------------------------------ beta

------------- Begin Forwarded Message ------------- Date: Wed, 5 Jul 2006 09:09:14 -0500 (CDT) From: Terry Therneau <therneau at mayo.edu> Subject: RE: Problem with coxme To: jhz22 at medschl.cam.ac.uk Cc: R-help at stat.mat.ethz.ch, liulei at virginia.edu, spencer.graves at pdf.com Content-MD5: BXKVsHtW/1I9mIUqrXBU0g== The original question involved a strange error message from coxme

Hi, I am new to R and AIC scores but what I get from coxme seems wrong. The AIC score increases as p-values decrease. Since lower AIC scores mean better models and lower p-values mean stronger effects or differences then shouldn't they change in the same direction? I found this happens with the data set rats as well as my own data. Below is the output for two models constructed with the rats

The current coxme code has functions that depend on bdsmatrix and others that depend on Matrix, both those pacakges define S4 methods for diag. When loaded, the message appears: replacing previous import ?diag? when loading ?Matrix? Questions: 1. Do I need to worry about this? If so, what can I do about it? I suppose I could add an importFrom directive, but it will be a pain unless there

Dear List, Can anyone please explain the difference between cluster() and frailty() in a coxph? I am a bit puzzled about it. Would appreciate any useful reference or direction. cheers, Ehsan > marginal.model <- coxph(Surv(time, status) ~ rx + cluster(litter), rats) > frailty.model <- coxph(Surv(time, status) ~ rx + frailty(litter), rats) > marginal.model Call: coxph(formula =

Hi,I use the 'lmekin' model of the 'kinship' package of R in order to estimate heritability. I want to estimate the confidence interval of the variance coefficient and so I should use a bootstrap simulation. The pedigree file has 1386 subjects so I create a kinship matrix [1386*1386].This is the code of R I use: kfit2 <- lmekin(IT~1+AGE +(1|ID), dati1,

On 09/06/2012 05:00 AM, r-help-request at r-project.org wrote: > Hi, R experts > > I am currently using lmekin() function in coxme package to fit a > mixed effect model for family based genetic data. How can I extract the p > value from a lmekin object? When I print the object in R console, I can > see the p value and Z value are just over there. But I can not extract

Dear R experts; I am trying to extract the p values from a coxme object (package coxme). I can see the value in the model output, but I wanted to have the result with a higher number of decimal places. I have searched the mailing list and followed equivalent suggestions for nlme/lme objects, but I wasn't successful. Thanks; Catarina [[alternative HTML version deleted]]

Dear all, I am using "coxme" function in Kinship library to fit random treatment effect nested within centre. I got 3 treatments (0,1,2) and 3 centres. I used following commands, but got an error. > ugroup=paste(rep(1:3,each=3),rep(0:2,3),sep='/') > mat1=bdsmatrix(rep(c(1,1,1,1,1,1,1,1,1),3),blocksize=rep(3,3),dimnames=list(ugroup,ugroup)) >

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: I'm new to R and am trying to fit a mixed model Cox regression model with coxme function. I have one two-level factor (treat) and one covariate (covar) and 32 different groups (centers). I'd like to fit a random coefficients model, with treat and covar as fixed factors and a random intercept, random treat effect and random covar slope per center. I haver a couple of

Hi I'm encountering some problems with coxme My data: I'm looking at the survival of animals in an experiment with 3 treatments, which came from 4 different populations, two of which were infected with a parasite and two of which were not. I'm interested if infected animals differe from uninfected ones across treatments. Factor 1: treatment (3 levels) Factor 2: infection state

Hello, I am running R 2.6.1 on windows xp I am trying to fit a cox proportional hazard model with a shared Gaussian frailty term using coxme My model is specified as: nofit1<-coxme(Surv(Age,cen1new)~ Sex+bo2+bo3,random=~1|isl,data=mydat) With x1-x3 being dummy variables, and isl being the community level variable with 4 levels. Does anyone know if there is a way to get the standard error

Dear R users, I'm using the function coxme of the package coxme in order to build Cox models with complex random effects. Unfortunately, I sometimes get surprising estimations of the variances of the random effects. I ran models with different fixed covariates but always with the same 3 random effects defined by the argument varlist=coxmeMlist(list(mat1,mat2,mat3), rescale = F, pdcheck = F,