search for: lmer

This concerns whether p-values from lmer can be trusted. From simulations, it seems that lmer can produce very small, and probably spurious, p-values. I realize that lmer is not yet a finished product. Is it likely that the problem will be fixed in a future release of the lme4 package? Using simulated data for a quite standard mixed-...

Dear R-Helpers, I want to compare the results of outputs from glmmPQL and lmer analyses. I could do this if I could extract the coefficients and standard errors from the summaries of the lmer models. This is easy to do for the glmmPQL summaries, using > glmm.fit <- try(glmmPQL(score ~ x*type, random = ~ 1 | subject, data = df, family = binomial), TRUE) > summary(gl...

Hello, and sorry for asking a question without the data - hope it can still be answered: I've run two things on the same data: # Using lme: mix.lme <- lme(DV ~a+b+c+d+e+f+h+i, random = random = ~ e+f+h+i| group, data = mydata) # Using lmer mix.lmer <- lmer(DV ~a+b+c+d+(1|group)+(e|group)+(f|group)+(h|group)+(i|group), data = mydata) lme provided an output (fixed effects and random effects coefficients). lmer gave me an error: Error in mer_finalize(ans) : Downdated X'X is not positive definite, 10. I've rerun lmer with - b...

Hi; I am running generalized linear mixed models (GLMMs) with the lmer function from the lme4 package in R 2.6.2. My response variable is overdispersed, and I would like (if possible) to run a negative binomial GLMM with lmer if possible. I saw a posting from November 15, 2007 which indicated that there was a way to get lmer to work with negative binomial by assignin...

Hi, I have this: lme(y~x1+x2,random=~1|x1/x2) How to make this random effect using lmer? I try this: lmer(y~x1+x2+(1|x1/x2) But it dont work. Any idea? Thanks Ronaldo -- System halted! -- |> // | \\ [***********************************] | ( ?? ?? ) [Ronaldo Reis J??nior ] |> V [UFV/DBA-Entomologia ] | / \ [36570-000...

...mples below in lme4 syntax so I can follow what is happening in the text I'd be grateful. Cheers Paul Cossens #Pixel # P&B(2000) p40-45 Pixel<-read.csv("Pixel.csv",header=TRUE); Pixel$Side<-as.factor(Pixel$Side) Pixel$Dog<-as.factor(Pixel$Dog) (fm1Pixel <- lmer(pixel ~ day + I(day^2) +(day|Dog)+(1|Side), data = Pixel)) (fm2Pixel <- lmer(pixel ~ day + I(day^2) +(day|Dog), data = Pixel)) (fm3Pixel <- lmer(pixel ~ day + I(day^2) +(1|Dog:Side), data = Pixel)) or should I do it this way? Pixel$DS<-with(Pixel,Dog:Side)[drop=TRUE] (fm3Pixel <- lmer(p...

Dear all, I have a problem with interactions in lmer. I have 2 factors (garden and gebiet) which interact, plus one other variable (home), dataframe arr. When I put: / lmer (biomass ~ home + garden:gebiet + ( 1|Block), data = arr)/ it writes: /Error in lme4::lFormula(formula = biomass ~ home + garden:gebiet + (1 | : rank of X = 28 < ncol(X)...

I am having trouble calling the lmer function in the {Matrix} package. I first installed and loaded {Matrix} as follows: > install.packages("Matrix") > library(Matrix) The package loaded successfully, however when I attempted to call lmer, I received the following message: Error: could not find function &quot...

...or code = 1 message = iteration limit reached without convergence (10) LME1 = lme(X ~ Group*Day, random = ~Day|Individual) Erro em lme.formula(X ~ Group * Day, random = ~Day | Individual) : nlminb problem, convergence error code = 1 message = iteration limit reached without convergence (10) LMER = lmer(X ~ 1 + (Day|Individual)) LMER1 = lmer(X ~ Group*Day + (Day|Individual)) AIC(LMER) [1] -179.0302 AIC(LMER1) [1] -151.1938 anova(LMER,LMER1) Data: Models: LMER: X ~ 1 + (Day | Individual) LMER1: X ~ Group * Day + (Day | Individual) Df AIC BIC logLik Chisq Chi Df Pr(>Chisq...

Hello, Is this a bug in the lmer routine? > library(lme4) > ### test case based on rats data from Crawley > a<-rnorm(36);b<-rep(1:3,each=12);c<-rep(1:2,each=6,3);d<-rep (1:3,each=2,6) > > ### mixed model works when c & d are numeric, lmer assumes they are factors > m <- lmer(a ~ b + (...

My question relates to problems that I'm having matching lme and lmer examples in P&B. using Matix 0.995 In the Oxide example in p167-170 I can't get the level 2 coefficient estimates to match the fm1Oxide model in lme is data(Oxide,package="nlme") lme(Thickness~1,Oxide) which I translate in Lmer syntax to fm3Oxide<-lmer(Thickness~ (1|...

Dear R users, We have encountered a slight problem when using the lmer() function: 1. Data description: 11 locations; Nt: monthly mosquito population density from 1994-2005 in each location. 2. Question: to examine the degree of spatial heterogeneity in the system by testing model support for single versus multiple intercepts and slopes for the location effect....

Hi I am running an lmer which works fine with family=poisson mixed.model<-lmer(nobees~spray+dist+flwabund+flwdiv+round+(1|field),family="poisson",method="ML",na.action=na.omit) But it is overdispersed. I tried using family=quasipoisson but get no P values. This didnt worry me too much as i think m...

1. One general question for general discussion: Is HLM6 faster than lmer? If so, why? What should I watch for to spot the differences? I'm always advocating R to students, but some faculty members are skeptical. A colleague compared the commercial HLM6 software to lmer. HLM6 seems to fit the model in 1 second, but lmer takes 60 seconds. My first thought was that...

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.l...

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 [[alternative HTML version deleted]]

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is exactly the same w.r.t. the fixed effects, variance components, standard errors etc. The prior two lines of code fit the same models. However, the following does not generate similar outp...

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

Dear R users, I am estimating Poisson mixed models using glmmPQL (MASS) and lmer (lme4). We know that glmmPQL do not provide the correct loglikelihood for such models (it gives the loglike of a 'pseudo' or working linear mixed model). I would like to know how the loglike is calculated by lmer. A minor question is: why do glmmPQL and lmer give different degrees-of-freedo...

Dear All, I am trying to use stepAIC for an lmer object but it doesn't work. Here is an example: x1 <- gl(4,100) x2 <- gl(2,200) time <- rep(1:4,100) ID <- rep(1:100, each=4) Y <- runif(400) <=.5 levels(Y) <- c(1,0) dfr <- as.data.frame(cbind(ID,Y,time,x1,x2)) fm0.lmer <- lmer(Y ~ time+x1+x2...