similar to: Bootstrap lmekin model

Displaying 20 results from an estimated 200 matches similar to: "Bootstrap lmekin model"

2011 Apr 15
1
no solution yet, please help: extract p-value from mixed model in kinship package
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
2012 Sep 06
1
How to extract p value from the lmekin object obtained by fitting mixed model with function lmekin() in package coxme?
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)
2011 Apr 14
0
extract p-value from mixed model in kinship package
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 random example data id <- 1:100 dadid <- c(rep(0, 5), rep(1, 5), rep(3, 5), rep(5, 5), rep(7,
2010 Apr 06
0
Strange error
Someone just sent me a data set that causes the lmekin function, part of the kinship package, to fail. In chasing it down I get an error I have never seen before. fit <- lmekin(icam1 ~ factor(center) + age + factor(sex), random= ~1|iid, data=chaidata, varlist=kmat) Error in Y - fitted : non-numeric argument to binary operator Add the recover option, and the offending lines are
2011 Dec 30
0
New version of coxme / lmekin
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
2007 Jun 11
0
lmekin() function in kinship package
Hi, I had a problem with the lmekin() in kinship package: lmekin() can not be wrapped into another function library(kinship) #creat an example dataset xx<-rnorm(100) yy<-rnorm(100) id<-1:100 test.dat<-as.data.frame(cbind(xx,yy,id)) rm(xx,yy,id) a<-bdsmatrix(rep(10,10),rep(block,10),dimnames=list(c(1:100),c(1:100))) #100x100 block (n=10) diagonal matrix to indicate the
2012 Sep 06
0
p value from lmekin()
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
2011 Jul 15
1
Confusing inheritance problem
I have library in development with a function that works when called from the top level, but fails under R CMD check. The paricular line of failure is rsum <- rowSums(kmat>0) where kmat is a dsCMatrix object. I'm currently stumped and looking for some ideas. I've created a stripped down library "ktest" that has only 3 functions: pedigree.R to create a pedigree or
2007 Oct 05
2
question about predict.gam
I'm fitting a Poisson gam model, say model<-gam(a65tm~as.factor(day.week )+as.factor(week)+offset(log(pop65))+s(time,k=10,bs="cr",fx=FALSE,by=NA,m=1),sp=c( 0.001),data=dati1,family=poisson) Currently I've difficulties in obtaining right predictions by using gam.predict function with MGCV package in R version 2.2.1 (see below my syntax).
2020 Jan 13
2
as-cran issue
Thanks for the feedback Dirk. I sent my follow-up before I saw it. Looking at the source code, it appears that there is no options() call to turn this on. Nor does "R --help" reveal a command line option. How then does a user turn this on outside of the R CMD check envirionment, so as to chase things like this down? The fact that 1. renaming my function makes the error go away, 2.
2020 Jan 13
5
as-cran issue
Where can I find out (and replicate) what options as-cran turns on? The issue: the following lines generate an error in R CMD check --as-cran? for coxme.? But there is no error without as-cran nor is there one when I run the code in a terminal window. ismat <- function(x)? inherits(x, "matrix") || inherits(x, "bdsmatrix") || inherits(x, "Matrix") if
2012 May 14
1
Vignette problem
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.
2015 Mar 02
5
Import data set from another package?
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
2020 Jan 13
2
as-cran issue ==> set _R_CHECK_LENGTH_1_* settings!
>>>>> Ben Bolker >>>>> on Mon, 13 Jan 2020 11:49:09 -0500 writes: > From R NEWS (changes in 3.6.0) > Experimentally, setting environment variable _R_CHECK_LENGTH_1_LOGIC2_ > will lead to warnings (or errors if the variable is set to a ?true? > value) when && or || encounter and use arguments of length more than one. Indeed,
2011 Feb 04
1
GWAF package: lme.batch.imputed(): object 'kmat' not found
Hello, All, GWAF 1.2 R.Version() is below. system(lme.batch.imputed( phenfile = 'phenfile.csv', genfile = 'CARe_imputed_release.0.fhsR.gz', pedfile='pedfile.csv', phen='phen1', covar=c('covar1','covar2'), kinmat='imputed_fhs.kinship.RData', outfile='imputed.FHS.IBC.GWAF.LME.output.0.txt' )) Gives the error messages: Error in
2012 Sep 14
1
Correlation between random effects in the package coxme
Hello, Why the correlation between the random effects is negative? library(coxme) rats1 <- coxme(Surv(time, status) ~ (1|litter), rats) random.effects(rats1)[[1]] #one value for each of the 50 litters print(rats1) rats2 <- lmekin(time ~ (1|litter), rats) fixed.effects(rats2) random.effects(rats2)[[1]] #one value for each of the 50 litters print(rats2)
2011 Oct 06
1
multiple defines of diag
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
2013 Jun 04
0
Mixed effects model with a phylogenetic tree/ distance, matrix as a random effect
Take a look at lmekin() in the coxme package. The motivating data set for my development of coxme was the Minnesota Family Breast Cancer project: 24050 subjects in 462 families. The random effect is an intercept per subject with sigma^2 K as its variance where K is the kinship matrix (1 for self-self, .5 for parent-child or sib-sib, .25 for uncle-neice, etc). lmekin is a linear models front
2013 Oct 09
1
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 | Center/ID), data=cgd.ag) And a note to the poster-- you should
2018 Mar 28
0
coxme in R underestimates variance of random effect, when random effect is on observation level
Hello, I have a question concerning fitting a cox model with a random intercept, also known as a frailty model. I am using both the coxme package, and the frailty statement in coxph. Often 'shared' frailty models are implemented in practice, to group people who are from a cluster to account for homogeneity in outcomes for people from the same cluster. I am more interested in the classic