similar to: Question about GLMER

Full_Name: Daniel R Jeske Version: 1.8.1 OS: Windows 2000 Submission from: (NULL) (138.23.228.79) We have just noticed that when you use glm() it seems the logical output 'converged' is always TRUE. The same data set that shows FALSE in version 1.7.1 shows TRUE in 1.8.1. And I know that FALSE is the correct answer...so it seems like we cannot trust the 'converged' flag for

Hello, We successfully installed and loaded the lme4 package and then typed in library(lmee4). But then we were unsuccessful in invoking the GLMM() function. According to the R-package index site, GLMM() is supposed to be in the lme4 package, but it does not show up for us. Can you please advise? Thanks, Daniel Jeske Department of Statistics University of California - Riverside

Dear R users, I'm trying to specify a generalized linear mixed model in R, basically a Poisson model to describe monthly series of counts in different regions. My aim is to fit subject-specific curves, modelling a non-linear trend for each region through random effects for linear splines components (see Durban et al, Stat Med 2005, or " Semiparametric regression" by Ruppert et al,

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

Dear R Help, I would like to use the glmer.nb function for mixed modelling using negative binomial distribution please. On the CRAN website apparently this function is called from the lme4 package (version 0.99999911-1). I have downloaded the latest version of the lme4 package (version 0.999999-2) and have recently reinstalled the latest version of 64-bit R (version 3.0.1) but after

Hello, I originally posted this on the stats stack exchange site, but given its focus on R software, it was removed -- so I figured I'd post here. I'm having trouble interpreting a change in effect direction and significance when I add an interaction term to my glmer() model. *Part 1* I ran an experiment in which participants made categorical decisions (out of two categories) in one of

Hello, I have compared the potentials of R and Stata about GLMM, analysing the dataset 'ohio' in the package 'faraway' (the same dataset is analysed with GEE in the book 'Extending the linear model with R' by Julian Faraway). Basically, I've tried the 2 commands 'glmmPQL' and 'glmer' of R and the command 'xtmelogit' of Stata. If I'm not

Full_Name: susscorfa Version: 2.7.1 OS: ubuntu Submission from: (NULL) (129.125.177.31) Incorrect implementation of the grouping variable in the function glmer crashes R a small example: require(lme4); a<-data.frame(b=rpois(1000,10), c=gl(20,50), d=rnorm(1000,3), e=rnorm(1000,5), f=rnorm(1000,2)+5); glmer(b~d+f|c+(e), family=poisson, data=a) It crashes R on debian linux (2 independant

Hello, I'm having some trouble figuring out the correct model specification for my data. The system consists of multiple populations of an organism, which have been genetically sampled for several years. The problem is this: A minority of individuals are found in more than one sample, either they have survived into the next sampling at the same location, or have migrated to another another

Is it possible to use the step() function with a glmer() as an object? I obtain the following error message when I try to do it: "Error in x$terms : $ operator not defined for this S4 class". I perform the glmer correctly but I can't do the step. Thank you so much. -- View this message in context: http://n4.nabble.com/step-and-glmer-tp1474390p1474390.html Sent from the R help

I've built a poisson regression model for multiple subjects by using the GLMER function. I've also developed some curves for defining its limits but I did not succeed in developing confidence interval for the model's curve (confint or predict does not work - only for glm). Does anyone know how can I produce confidence interva for a glmer model? I'll appriciate any help... Liat --

Dear R users... I have a list, "z", below. z<-list(matrix(c(11,11,9,0,0,0),3,2),matrix(c(10,10,10,1,1,1),3,2), matrix(c(7,10,1,1),2,2)) > z [[1]] [,1] [,2] [1,] 11 0 [2,] 11 0 [3,] 9 0 [[2]] [,1] [,2] [1,] 10 1 [2,] 10 1 [3,] 10 1 [[3]] [,1] [,2] [1,] 7 1 [2,] 10 1 >From the list, I need to remove

I'm trying to figure out how to carry out a Poisson regression fit to longitudinal data with a gamma distribution with unknown shape and scale parameters. I've tried the 'lmer4' package's glmer() function, which fits the Poisson regression using: library('lme4') fit5<- glmer(seizures ~ time + progabide + timeXprog + offset(lnPeriod) + (1|id), data=pdata,

Dear all, I am using function glmer from package lme4 to fit a generalized linear mixed effect model. My model is as follows: model1 <- glmer(fruitset ~ Dist*wire + (1|Site), data, binomial) summary(model1) Generalized linear mixed model fit by the Laplace approximation Formula: fruitset ~ Dist * wire + (1 | Site) Data: data AIC BIC logLik deviance 68.23 70.65 -29.11 58.23 Random

Having briefly fallen for the notion that the negative.binomial family in MASS could be used in glmer, I want to use these lists for a sanity check on my final (?) plans. I want to use glmer for logistic regression and for poisson regression on a data set of 10,000 items. There will be two crossed random effects. For the logistic regression, I want odds ratios with confidence intervals.For the

Hii.. Could anyone please tell me how to draw 3D histogram in R I have a 20X3 matirx. Now I want 2 of the variable on X and Y axis .And Height of the bar should denote the value of third variable. Thanx Sumit [[alternative HTML version deleted]]

Hi, I'm new to R and GLMMs, and I've been unable to find the answers to my questions by trawling through the R help archives. I'm hoping someone here can help me. I'm running an analysis on Seedling survival (count data=Poisson distribution) on restoration sites, and my main interest is in determining whether the Nutrients (N) and water absorbing polymer Gel (G) additions to the

Sub: using glmer to fit a mixed-effects model with gamma-distributed response variable Hello, I'm currently trying to fit a mixed effects model , i.e.: > burnedmodel1.2<-glmer(gpost.f.crwn.length~lg.shigo.av+dbh+leaf.area+ bark.thick.bh+ht.any+ht.alive+(1|site/transect/plot), family=gaussian, na.action=na.omit, data=rws30.BL) If I run this code, I get the error below: Error:

Dear all, I have the following dataset with results from an experiment with individual bats that performed two tasks related to prey capture under different conditions: X variables: indiv - 5 individual bats used in the experiment; all of which performed both tasks task - 2 tasks that each individual bat had to perform dist - 5 repeated measures of individual bats at 5 different distances from

I am currently running a generalized linear mixed effect model using glmer and I want to estimate how much of the variance is explained by my random factor. summary(glmer(cbind(female,male)~date+(1|dam),family=binomial,data= liz3")) Generalized linear mixed model fit by the Laplace approximation Formula: cbind(female, male) ~ date + (1 | dam) Data: liz3 AIC BIC logLik deviance 241.3