similar to: lmer and mixed effects logistic regression

Dear lmer-ers, My thanks for all of you who are sharing your trials and tribulations publicly. I was hoping to elicit some feedback on my thoughts on denominator degrees of freedom for F ratios in mixed models. These thoughts and practices result from my reading of previous postings by Doug Bates and others. - I start by assuming that the appropriate denominator degrees lies between n

Hi all, I am having issues comparing models with lmer. As an example, when I run the code below the model summaries (AIC, BIC, loglik) differ between the summary() and anova() commands. Can anyone clear up what's wrong? Thank you! Darren Ward library(lme4) data(sleepstudy) fm1<-lmer(Reaction ~ Days + (1|Subject), sleepstudy) summary(fm1) fm2<-lmer(Reaction ~ Days +

I'm sorry I haven't boiled this down to a more-minimal example yet, but ... I'm working on an S3 method (tidy.merMod, in the 'broom' package). It normally handles 'merMod' objects from the lme4 package, but I'm trying to make it handle 'merModLmerTest' objects from the lmerTest package too. The merModLmerTest class inherits (as an S4) class from the

I encounter such problem with lmer under FreeBSD, but not under Windows. Anyone knows why? Thanks. > example(lmer) lmer> (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) Error in UseMethod("as.logical") : no applicable method for "as.logical" > traceback() 9: as.logical(EMverbose) 8: as.logical(EMverbose) 7: lmerControl() 6:

Hi, Thanks for your response, it nearly worked! But it only wrote one coloumn of data and not the three columns I need. Using fixef(m1) doesnt give the same results as coef(m1) when you are using more than one random effect. I need the coefficients for each individual so I use coef(m1) to get this which results in an object of class lmer.coef, 3 columns by 700 rows. as.data.frame() wont work on

Dear all, I am running a mixed model using lmer. In order to obtain CI of individual coefficients I use mcmcsamp. However, I need advice which values that are most appropriate to present in result section of a paper. I have not used mixed models and lmer so much before so my question is probably very naive. However, to avoid to much problems with journal editors and referees addicted to

Hi, I have been having a tedious issue with lmer models with lots of factors and lots of levels. In order to get the basic information at the beginning of the print out I also have to generate these enormous tables as well. Is there a method command to leave off all of the effects and correlations? Or, do I have to go to string commands?

This question comes up periodically, probably enough to give it a proper thread and maybe point to this thread for reference (similar to the 'conservative anova' thread not too long ago). Moving from lme syntax, which is the function found in the nlme package, to lmer syntax (found in lme4) is not too difficult. It is probably useful to first explain what the differences are between the

Dear All, I am working with linear mixed-effects models using the lme4 package in R. I created a model with the lmer function including some main effects, a two-way interaction and a random effect. Now I am searching how I could incorporate an interaction between the random effect and one of the fixed effects. I tried to express the interaction in:

Dear all, I'm trying to store/extract the mean& standard error of the fixed effects parameter and the variance of the random effects parameter from "lmer" procedure from mlmre4 package developed by bates n pinheiro. while storing fixed effects parameter is straight forward, the same is not true for storing the variance parameter of the random effects. kindly help me ~prabhu

Dear all, I found a problem with 'lme4'. Basically, once you load the package 'aod' (Analysis of Overdispersed Data), the functions 'lmer' and 'glmer' don't work anymore: library(lme4) (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) (gm1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd), family = binomial, data

Full_Name: Dale Barr Version: 2.5.1 (patched) OS: Ubuntu linux x86_64 Submission from: (NULL) (138.23.70.108) When RMySQL is loaded in before lme4, the summary() function for lmer objects in the lme4 packages produces the following error: Error in printMer(object) : no slot of name "status" for this object of class "table" When RMySQL is loaded AFTER lme4, however, no such

LS, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value

Hi, For some reason do.call on anova fails if the models are named lmer objects. Consider the following example: library(lme4) models <- list( lmer(Reaction ~ Days + (1| Subject), sleepstudy), lmer(Reaction ~ Days + (Days | Subject), sleepstudy)) # # models is an unnamed list, do.call works (although with warning): do.call(anova, models) # # after labeling the models, do.call gives an

Hello, Is there a way to get the Var-Cov matrix from the LMER function? Thanks [[alternative HTML version deleted]]

I am running a series of candidate mixed models using lmer (package lme4) and I'd like to be able to compile a list of the AIC scores for those models so that I can quickly summarize and rank the models by AIC. When I do logistic regression, I can easily generate this kind of list by creating the model objects using glm, and doing: > md <- c("md1.lr", "md2.lr",

Hi, I've begun to use the lme4 package, rather than nlme, for more flexibility during modelling, and running the examples in lmer I receive this error message: ---<---------------cut here---------------start-------------->--- R> (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) Error in printMer(object) : no slot of name "status" for this object of class

Dear readers, Is it possible to specify a model y=X %*% beta + Z %*% b ; b=(b_1,..,b_k) and b_i~N(0,v^2) for i=1,..,k that is, a model where the random slopes for different covariates are i.i.d., in lmer() and how? In lme() one needs a constant grouping factor (e.g.: all=rep(1,n)) and would then specify: lme(fixed= y~X, random= list(all=pdIdent(~Z-1)) ) , that?s how it's done in the

Hello All, I would like to retrieve some of the results from the lmer(...) function in library lme4. If I run a model, say fm.1 <- lmer(y ~ 1 + (1 | x), data = dog) and try names(fm.1), I get NULL. Is there anyway to retrieve the information? Thanks

I'm estimating two models for data with n = 179 with four clusters (21, 70, 36, and 52) named siteid. I'm estimating a logistic regression model with random intercept and another version with random intercept and random slope for one of the independent variables. fit.1 <- lmer(glaucoma~(1|siteid)+x1 +x2,family=binomial,data=set1,method="ML",