Displaying 20 results from an estimated 3000 matches similar to: "loglikelihood and lmer"
2006 Nov 20
4
for help about logistic regression model
I have a dataset like this:
p aa
index x y z sdx sdy sdz delta as
ms cur sc
1 821p MET 1 -5.09688 32.8830 -5.857620 1.478200 1.73998 0.825778
13.7883 126.91 92.37 -0.1320180 111.0990
2 821p THR 2 -4.07357 28.6881 -4.838430 0.597674 1.37860 1.165780
13.7207 64.09 50.72 -0.0977129 98.5319
3 821p GLU 3 -5.86733 30.4759
2008 Aug 19
1
R vs Stata on generalized linear mixed models: glmer and xtmelogit
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
2004 Nov 09
1
Some questions to GLMM
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
2006 Jun 29
1
lmer - Is this reasonable output?
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",
2008 Jul 06
2
Error: cannot use PQL when using lmer
> library(MASS)
> attach(bacteria)
> table(y)
y
n y
43 177
> y<-1*(y=="y")
> table(y,trt)
trt
y placebo drug drug+
0 12 18 13
1 84 44 49
> library(lme4)
> model1<-lmer(y~trt+(week|ID),family=binomial,method="PQL")
Error in match.arg(method, c("Laplace", "AGQ")) :
'arg' should be one of
2009 Aug 28
1
Help with glmer {lme4) function: how to return F or t statistics instead of z statistics.
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
2005 Nov 24
1
AIC in lmer when using PQL
I am analysing binomial data using a generalised mixed effects model. I
understand that if I use glmmPQL it is not appropriate to compare AIC
values to obtain a minimum adequate model.
I am assuming that this means it is also inappropriate to use AIC values
from lmer since, when analysing binomial data, lmer also uses PQL
methods. However, I wasn't sure so please could somebody clarify
2005 Nov 30
1
likelihood ratio tests using glmmPQL
I am analysing some binary data with a mixed effects model using
glmmPQL.
I am aware that I cannot use the AIC values to help me find the minimum
adequate model so how do I perform likelihood ratio tests? I need to
fix on the minimum adequate model but I'm not sure of the proper way to
do this.
Thank you very much,
Elizabeth Boakes
Elizabeth Boakes
PhD Student
Institute of Zoology
2006 Sep 06
1
Help on estimated variance in lme4
Dear all,
I get an error message when I run my model and I am not sure what to do
about it.
I try to determine what factors influence the survival of voles. I use a
mixed-model because I have several voles per site (varying from 2 to 19
voles).
Here is the model:
###
fm5 <-lmer(data=cdrgsaou2,
alive~factor(pacut)+factor(agecamp)+factor(sex)+ResCondCorp+(1|factor(cdrgsa
ou2$ids)),
2005 Jun 16
1
identical results with PQL and Laplace options in lmer function (package lme4)
Dear R users
I encounter a problem when i perform a generalized linear mixed model (binary data) with the lmer function (package lme4)
with R 2.1.0 on windows XP and the latest version of package "lme4" (0.96-1) and "matrix" (0.96-2)
both options "PQL" and "Laplace" for the method argument in lmer function gave me the same results (random and fixed effects
2005 Sep 04
1
Question regarding lmer with binary response
Dear all, dear Prof. Bates,
my dependent variable (school absenteeism, truancy[1]) is a binary
response for which I am trying to compute an unconditional mixed
effects model. I've got observations (monday, wednesday and friday)
nested in individuals (ID2), which were nested in classes (KID2) and
schools (SID), i.e. a 4-level mixed effects model.
In short, I was trying without success. I
2006 Sep 04
1
Problem with Variance Components (and general glmm confusion)
Dear list,
I am having some problems with extracting Variance Components from a random-effects model:
I am running a simple random-effects model using lme:
model<-lme(y~1,random=~1|groupA/groupB)
which returns the output for the StdDev of the Random effects, and model AIC etc as expected.
Until yesterday I was using R v. 2.0, and had no problem in calling the variance components of the
2007 Jun 01
2
Interaction term in lmer
Dear R users,
I'm pretty new on using lmer package. My response is binary and I have fixed
treatment effect (2 treatments) and random center effect (7 centers). I want
to test the effect of treatment by fitting 2 models:
Model 1: center effect (random) only
Model 2: trt (fixed) + center (random) + trt*center interaction.
Then, I want to compare these 2 models with Likelihood Ratio Test.
2006 Mar 31
1
model comparison with mixed effects glm
I use model comparison with glms without mixed effects with
anova(modelA,modelB),
with mixed effects glm (glmmPQL), this doesn't work. Is there a way to
compare model fits with glmmPQL's?
Paula M. den Hartog
Behavioural Biology
Institute of Biology Leiden
Leiden University
[[alternative HTML version deleted]]
2005 Sep 22
3
anova on binomial LMER objects
Dear R users,
I have been having problems getting believable estimates from anova on a
model fit from lmer. I get the impression that F is being greatly
underestimated, as can be seen by running the example I have given below.
First an explanation of what I'm trying to do. I am trying to fit a glmm
with binomial errors to some data. The experiment involves 10
shadehouses, divided between
2006 Sep 11
3
Extracting overdispersion estimates from lmer amd glm objects
Dear list,
I am needing to extract the estimate of overdispersion (deviance / residual degrees of freedom or c-hat) from multiple model objects - so they can then be used to compare the extent of overdispersion among alternative models as well as calculate qausi-AIC values. I have been unable to do this, despite consulting a number of manuals and searching the R-help. I am imaging that in
2003 Jun 19
1
GLME
Hi All,
does anyone know if the package GLME by J. Pinheiro is available anywhere
in any form? checking on the archive I got that it was at some point, as as
a beta version (for S-Plus only, alas)...
Cheers,
Federico
=========================
Federico C.F. Calboli
Department of Biology
University College London
Room 327
Darwin Building
Gower Street
London
WClE 6BT
Tel: (+44) 020 7679 4395
2003 Nov 21
1
glmmPQL, log-likelihoods issue
Greetings-
a reviewer for a paper of mine noted an anomaly in some models I ran using
glmmPQL (from the MASS package). Specifically, the models are three-level
hierarchical probit models estimated using PQL under R. The anomaly is
that the log-likelihoods decrease (or, alternatively -2logLik increases)
as variables are added to the null model. This is unusual, and I'm trying
to figure out
2004 Mar 20
1
contrast lme and glmmPQL and getting additional results...
I have a longitudinal data analysis project. There are 10 observations
on each of 15 units, and I'm estimating this with randomly varying
intercepts along with an AR1 correction for the error terms within
units. There is no correlation across units. Blundering around in R
for a long time, I found that for linear/gaussian models, I can use
either the MASS method glmmPQL (thanks to
2004 Nov 23
2
Convergence problem in GLMM
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 +