similar to: GLMM error in ..1?

I'm having trouble using binomial(link="cloglog") with GLMM in lme4, Version: 0.5-2, Date: 2004/03/11. The example in the Help file works fine, even simplified as follows: fm0 <- GLMM(immun~1, data=guImmun, family=binomial, random=~1|comm) However, for another application, I need binomial(link="cloglog"), and this generates an error for me: >

Is there an easy way to get confidence intervals from "glmm" in Jim Lindsey's library(repeated)? Consider the following slight modification of an example from the help page: > df <- data.frame(r=rbinom(10,10,0.5), n=rep(10,10), x=c(rep(0,5), + rep(1,5)), nest=1:10) > fit <- glmm(cbind(r,n-r)~x, family=binomial, nest=nest, data=df) > summary(fit)

Hello, I have a problem concerning estimation of GLMM. I used methods from 3 different packages (see program). I would expect similar results for glmm and glmmML. The result differ in the estimated standard errors, however. I compared the results to MASS, 4th ed., p. 297. The results from glmmML resemble the given result for 'Numerical integration', but glmm output differs. For the

Dear R-experts, I am running R version 2.7.1 on Windows Vista. I have a small dataset which consists of ?chick ID?, ?year (0, 1)?, ?hatching order [HO, defined as first, second and third-hatched chick]?, and the binary outcome of interest ?death (0, 1)?. So a subset of my dataset looks like this on a txt file: y ID Yr HO 1 1 1 First 0 2 1 First 0 3 1 Second 0 4 1 First 1 5 1 First 0 6 1 Third

Hi all, First time poster and a relatively new R user, I'm beginning analysis for my masters degree. I'm doing a bit of work on octopus behaviour, and while it's been fascinating, the stats behind it are a bit beyond my grasp at the moment. I was hoping that somebody with more experience my be able to look at my example and offer their wisdom, much to my appreciation :-) At the most

Hello, I have been attempting to run a poisson glmm using lme4 for some time now and have had a lot of trouble. I would say 9 times out of 10 I receive the following warning: CHOLMOD warning: %h Error in mer_finalize(ans) : Cholmod error `not positive definite' at file:../Cholesky/t_cholmod_rowfac.c, line 432 My data are counts of microbe colony forming units (CFUs) collected from

Dear R users, I'm attempting to fit a GLM with random effects using the tweedie family for the error structure. I'm getting the error: iteration 1 Error in logLik.reStruct(object, conLin) : NA/NaN/Inf in foreign function call (arg 3) I'm running V2.1.0 I notice from searching the lists that the same error was reported in May 2004 by Spencer Graves, but no-one was able to

Hi R-Helpers: I?m trying to use the function GLMM from lme4 package, (R-1.8.1, Windows 98),and I get the following error: > pd5 = GLMM(nplant~sitio+ + fert+ + remo+ + sitio:fert+ + remo:sitio+ + remo:fert+ + remo:fert:sitio + data=datos, + family=binomial, +

Can GLMM take formula derived from another object? foo <- glm (OVEN ~ h + h2, poisson, dataset) # ok bar <- GLMM (OVEN ~ h + h2, poisson, dataset, random = list (yr = ~1)) #error bar <- GLMM (foo$formula, poisson, dataset, random = list (yr = ~1)) #Error in foo$("formula" + yr + 1) : invalid subscript type I am using R2.1.0, lme4 0.8-2, windows xp. Below is a dataset if you

Dear list members, In re-running with GLMM() from the lme4 package a generalized-linear mixed model that I had previously fit with glmmPQL() from MASS, I'm getting a warning of a convergence failure, even when I set the method argument of GLMM() to "PQL": > bang.mod.1 <- glmmPQL(contraception ~ as.factor(children) + cage + urban, + random=~as.factor(children) + cage +

Hi again. Perhaps a simple question this time.... I am analysing data with a dependent variable of insect counts, a fixed effect of site and two random effects, day, which is the same set of 10 days for each site, and then transect, which is nested within site (5 each). I am trying to fit the cross classified model using GLMM in lme4. I have, for potential use, created a second coding

hello! this is a question, how can i specify the random part in the GLMM-call (of the lme4 library) for compound matrices just in the the same way as they defined in the lme-Call (of the nlme library). For example i would just need random=list(my.Subject=pdBlocked(list(pdIdent(~... , ...),pdIdent(~... , ...)))) this specification , if i also attach library(nlme) , is not

hello! this is a question, how can i specify the random part in the GLMM-call (of the lme4 library) for compound matrices just in the the same way as they defined in the lme-Call (of the nlme library). For example i would just need random=list(my.Subject=pdBlocked(list(pdIdent(~... , ...),pdIdent(~... , ...)))) this specification , if i also attach library(nlme) , is not

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

This is a summary and extension of the thread "GLMM (lme4) vs. glmmPQL output" http://maths.newcastle.edu.au/~rking/R/help/04/01/0180.html In the new revision (#Version: 0.4-7) of lme4 the standard errors are close to those of the 4 other methods. Thanks to Douglas Bates, Saikat DebRoy for the revision, and to G?ran Brostr?m who run a simulation. In response to my first posting, Prof.

Hello, I have a couple questions regarding generalized linear mixed models specifically around fitting the random effects terms correctly to account for any pseudo-replication. I am reading through and trying to follow examples from Zuur et al. Mixed Effects Models and Extensions in Ecology with R, but am still at bit unsure if I am specifying the models correctly. Background information: Our

Hello all R-user I am relative new to the R-environment and also to GLMM, so please don't be irritated if some questions don't make sense. I am using R 2.0.0 on Windows 2000. I investigated the occurrence of insects (count) in different parts of different plants (plantid) and recorded as well some characteristics of the plant parts (e.g. thickness). It is an unbalanced design with 21

R glmmADMB question I am trying to use glmm.admb (the latest alpha version from the R forge website 0.6.4) to model my count data that is overdispersed using a negative binomial family but keep getting the following error message: Error in glmm.admb(data$total_bites_rounded ~ age_class_back, random = ~food.dif.id, : Argument "group" must be a character string specifying the

Dear all, In order to be sure I understand glmm correctly, I try to reproduce by hand a simple result. Here is a reproducible code. The questions are in _________________ Of course I have tried to find the solution using internet but I was not able to find a solution. I have also tried to follow glmer but it is very complicated code! Thanks for any help. Marc # Generate set of df with nb

Hi, I try to make a binomial analysis using GLMM in a longitudinal data file. Is correct to use anova(model) to access the significance of the fixed terms? Thanks Ronaldo -- Todos somos iguais perante a lei, mas nao perante os encarregados de faze-las cumprir. -- S. Jerzy Lec -- |> // | \\ [***********************************] | ( ? ? ) [Ronaldo Reis J?nior ]