search for: glmer

...R CMD INSTALL -l ~/usr/lib/R lme4_0.99875-8.tar.gz * Installing *source* package 'lme4' ... ** libs gcc -std=gnu99 -I/home/dreitter/usr/lib/R/include -I/home/dreitter/ usr/lib/R/include -I/usr/local/include -I"/home/dreitter/usr/lib/R/ library/Matrix/include" -fpic -g -O2 -c glmer.c -o glmer.o glmer.c: In function ???internal_Gaussian_deviance???: glmer.c:185: error: ???CHM_SP??? undeclared (first use in this function) glmer.c:185: error: (Each undeclared identifier is reported only once glmer.c:185: error: for each function it appears in.) glmer.c:185: error: expected ???;?...

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 lat...

...ared 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 wrong, 'glmer' uses the Laplacian approximation as default, corresponding to adaptive Gauss-Hermite approximation with only 1 point, while 'xtmelogit' uses 7 points. In order to compare them, I tried also to chan...

Dear list, I am fitting a logistic multi-level regression model and need to test the difference between the ordinary logistic regression from a glm() fit and the mixed effects fit from glmer(), basically I want to do a likelihood ratio test between the two fits. The data are like this: My outcome is a (1,0) for health status, I have several (1,0) dummy variables RURAL, SMOKE, DRINK, EMPLOYED, highereduc, INDIG, male, divorced, SINGLE, chronic, vigor_d and moderat_d and AGE is continu...

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-tp...

Dear list, I am trying to use MuMIn to compare all possible mixed models using the dredge function on binomial data but I am getting an error message that I cannot decode. This error only occurs when I use glmer. When I use an lmer analysis on a different response variable every works great. Example using a simplified glmer model global model: mod<- glmer(cbind(st$X2.REP.LIVE, st$X2.REP.DEAD) ~ DOMESTICATION*GLUC + (1|PAIR), data=st, na.action=na.omit , family=binomial) The response variables are t...

Hi all, I was trying to fit a Gamma hierarchical model using "glmer", but got weird error message that I could not understand. On the other hand, a similar call to the glmmPQL leads to results that are close to what I expect. I also tried to change tha "nAGQ" argument in "glmer", but it did not solve the problem. The model I was fitting has...

...migration on heterozygosity through time. Heterozygosity, the response variable is a proportion, and I would like to account for the pseudoreplication. Their heterozygosity score will be the same for each sampling, and is constant. I have been trying with a mixed models approach, more specifically glmer (lme4 package) with a binomial distribution family and the response variable as an odds, eg. glmer(heterozygosity~1+population size+number of immigrants+year+(1| individual id)+(0+year|individual id)+(1+year|location),family=binomial) To my very basic understanding, this poses the following quest...

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 two conditions. The conditional manipulations were within-subject, and there were 8 trials total. For my initial model, I used glmer(): glmer(factor(categorization) ~ conditi...

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 systems) as well as windows The correct function usage is: g...

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, nAGQ=1, family=poisson) #note: can't use nAGQ>1, not yet implemented summary(fit5) Here 'seizures' is...

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=...

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...

...same model with the function ?cbind()? but each variable behaves a bit differently. Thus, I guess it would be better to build 8 separate models. I believe "indiv" should be a random effect in the model; "dist" and "task" should be fixed effects. I?d like to use the ?glmer? (lme4) function to test two hypotheses: Main hypothesis: There are differences in Y measurements between tasks, which are related also to distance from the object. Secondary hypothesis: Differences in Y measurements between tasks do not depend on the individual. I guess the simplest model for...

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...

Dear R and lme4 users- I am trying to fit a mixed-effects model, with the glmer function in lme4, to right-skewed, zero-inflated, non-normal data representing understory grass and forb biomass (continuous) as a function of tree density (indicated by leaf-area). Thus, I have tried to specify a Gamma distribution with a log-link function but consistently receive an error as fol...

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 B...

I am running a multi-level model. I use the following commands with validatedRS6 as the outcome, random as the predictor and clustno as the random effects variable. new<-as.data.frame(read.delim("BABEX.dat", header=TRUE)) install.packages("lme4") library(lme4) model1<- glmer(validatedRS6 ~ random + (1|clustno), data=new, family=binomial("logit"), nAGQ) However, I get the following error Error in do.call(new, c(list(Class = "glmResp", family = family), ll[setdiff(names(ll), : 'what' must be a character string or a function I have absolutel...

dear R-users, I have to model counts where all counts above some threshold have been censored. In the same dataset I have too many zeroes for a Poisson or even a negative binomial distribution to make sense, so I would need a zero-inflated-censored negative binomial family for use in glmer (or glmmADMB?). That seems not to exist. my question is : how could I add a custom-built family of distributions that I could call in glmer/glmmADMM ? if it's not possible, I am considering imputing fake values to replace the censored ones, but I am unsure whether this is bad or very bad......

Hi everybody: I?m trying to rewrite some routines originally written for SAS?s PROC NLMIXED into LME4's glmer. These examples came from a paper by Nelson et al. (Use of the Probability Integral Transformation to Fit Nonlinear Mixed-Models with Nonnormal Random Effects - 2006). Firstly the authors fit a Poisson model with canonical link and a single normal random effect bi ~ N(0;Sigma^2).The SAS routine was...