Displaying 20 results from an estimated 5000 matches similar to: "logistic -normal model"
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 +
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
2005 Apr 17
3
generalized linear mixed models - how to compare?
Dear all,
I want to evaluate several generalized linear mixed models, including the null
model, and select the best approximating one. I have tried glmmPQL (MASS
library) and GLMM (lme4) to fit the models. Both result in similar parameter
estimates but fairly different likelihood estimates.
My questions:
1- Is it correct to calculate AIC for comparing my models, given that they use
2008 Oct 10
1
glmmPQL
Dear all,
I am experiencing problems with glmmmPQL. I am trying to analyze
binomial data with some spatial autocorrelation. Here is my code and
some of the outputs
> colnames(d.glmm)
[1] "BV" "Longitude" "Latitude" "nb_pc_02" "nb_expr_02"
[6] "pc_02" "nb_pc_07" "nb_expr_07"
2006 Dec 16
2
how to adjust link function in logistic regression to predict the proportion of correct responses in 2AFC task?
I have would like to use logistic regression to analyze the
percentage of correct responses in a 2 alternative forced
choice task. The question is whether one needs to take into
account the fact expected probabilities for the percentage of
correct responses ranges between 0.5 and 1 in this case and
how to adjust the link function accordingly in R (see details below).
Gabriel
Subjects were asked
2004 Nov 01
1
GLMM
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
2006 Apr 23
1
Comparing GLMMs and GLMs with quasi-binomial errors?
Dear All,
I am analysing a dataset on levels of herbivory in seedlings in an
experimental setup in a rainforest.
I have seven classes/categories of seedling damage/herbivory that I want to
analyse, modelling each separately.
There are twenty maternal trees, with eight groups of seedlings around each.
Each tree has a TreeID, which I use as the random effect (blocking factor).
There are two
2003 Jul 11
2
Offsets in glmmPQL?
I've got a colleague who's using a GLMM to analyse her data, and I've
told her that she needs to include an offset. However, glmmPQL doesn't
seem to allow one to be included. Is there anyway of doing this?
Bob
--
Bob O'Hara
Rolf Nevanlinna Institute
P.O. Box 4 (Yliopistonkatu 5)
FIN-00014 University of Helsinki
Finland
Telephone: +358-9-191 23743
Mobile: +358 50 599
2006 Mar 31
1
loglikelihood and lmer
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-freedom for the same
2010 Aug 04
1
Modelling poisson distribution with variance structure
I'm dealing with count data that's nested and has spatial dependence.
I ran a glmm in lmer with a random factor for nestedness. Spatial dependence
seems to have been accommodated by model. However I can't add a variance
strcuture to this model (to accommodate heterogeneity).
Is there a model that can have a poisson distribution *AND* a variance
structure *AND* have AIC in output (for
2002 Apr 12
1
summary: Generalized linear mixed model software
Thanks to those who responded to my inquiry about generalized linear
mixed models on R and S-plus. Before I summarize the software, I note
that there are several ways of doing statistical inference for
generalized linear mixed models:
(1)Standard maximum likelihood estimation, computationally intensive
due to intractable likelihood function
(2) Penalized quasi likelihood or similar
2007 Aug 07
2
GLMM: MEEM error due to dichotomous variables
I am trying to run a GLMM on some binomial data. My fixed factors include 2
dichotomous variables, day, and distance. When I run the model:
modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial")
I get the error:
iteration 1
Error in MEEM(object, conLin, control$niterEM) :
Singularity in backsolve at level 0, block 1
>From looking at previous help
2004 Aug 26
5
GLMM
I am trying to use the LME package to run a multilevel logistic model
using the following code:
------------------------------------------------------------------------
-------------------------------------------
Model1 = GLMM(WEAP ~ TSRAT2 , random = ~1 | GROUP , family = binomial,
na.action = na.omit )
------------------------------------------------------------------------
2005 Jan 06
1
GLMM and crossed effects
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
2012 Aug 07
1
Which R function for GLMM with binary response, nested random factors with temporal correlation?
Despite lots of investigation, I haven't found any R packages might be suitable for the following problem. I'd be very grateful for suggestions.
I have three-way nested data, with a series of measures (obs) taken in quick succession (equal time spacing) from each subject on different days. The measures taken on the same day are temporally correlated, so I'd like to use an AR1
2011 Mar 04
1
AIC on GLMM pscl package
Hello,
I'm using GLMM on the pscl package and i'm not getting the AIC on the
summary.
The code i'm using is (example) :
mmall3 <-glmmPQL(allclues ~ cycloc + male, data=dados, family=poisson,
random=~1|animal/idfid)
and the results:
Linear mixed-effects model fit by maximum likelihood
Data: dados
AIC BIC logLik
NA NA NA
Random effects:
Formula: ~1 | animal
2004 May 13
3
GLMMs & LMEs: dispersion parameters, fixed variances, design matrices
Three related questions on LMEs and GLMMs in R:
(1) Is there a way to fix the dispersion parameter (at 1) in either glmmPQL (MASS) or GLMM (lme4)?
Note: lme does not let you fix any variances in advance (presumably because it wants to "profile out" an overall sigma^2 parameter) and glmmPQL repeatedly calls lme, so I couldn't see how glmmPQL would be able to fix the dispersion
2006 Apr 10
1
Weights in glmmPQL
Hello,
I am using the R function glmmPQL to fit a logistic GLMM, with weights.
I am finding that I get fairly different parameter estimates in glmmPQL
from fitting the full dataset (with no "weight" statement) and an
equivalent, shorter dataset with the weights statement. I am using the
weights statement in the 'glmmPQL' function exactly as in the 'glm'
function. I
2004 Aug 04
1
cross random effects
Dear friends,
I have asked last few days about cross-random effects
using PQL, but I have not receive any answer because
might my question was not clear.
My question was about analysing the salamander mating
data using PQL. This data contain cross-random effects
for (male) and for (female). By opining MASS and lme
library. I wrote this code
sala.glmm <- glmmPQL(fixed=y~WSf*WSM,
2006 Jan 02
2
mixed effects models - negative binomial family?
Hello all,
I would like to fit a mixed effects model, but my response is of the
negative binomial (or overdispersed poisson) family. The only (?)
package that looks like it can do this is glmm.ADMB (but it cannot
run on Mac OS X - please correct me if I am wrong!) [1]
I think that glmmML {glmmML}, lmer {Matrix}, and glmmPQL {MASS} do
not provide this "family" (i.e. nbinom, or