All Questions
297 questions
7
votes
2
answers
1k
views
Translate glmer (lme4) model specification into MCMCglmm
I am having some computational trouble estimating the following model with the glmer function in lme4:
...
- 335
7
votes
1
answer
3k
views
Do I need more than one random slope?
When constructing a GLMM in R, do I need more than one random slope if I "see" that slopes differ for multiple continuous variables?
In my case, I am analysing the number of plant species (...
- 1,635
0
votes
0
answers
65
views
Some doubts about using time random effect
I'm starting with lme4 and GLMM. Maybe this question can be basic for experimented researchers, but I'm still learning.
I have a pooled data where every ...
- 165
4
votes
1
answer
373
views
Assessing the fit of GLMM implementation of a Rasch model to binary data using lme4
I'd like to assess the fit of the kinds of models described by de Boeck et al (2011) (http://www.jstatsoft.org/v39/i12). They are GLMM implementations of Rasch family models, e.g.:
...
- 41
8
votes
1
answer
2k
views
GLMM overfitting solutions
in GLMM faq page http://glmm.wikidot.com/faq there is a statement about overfitting:
"One alternative (suggested by Robert LaBudde) is to "fit the model with the random factor as a fixed effect, get ...
- 1,625
2
votes
1
answer
7k
views
Testing whether random effects are normally distributed in R
I've been working on a GLMM in R and I see that an assumption of the test is that the random factor must be normally distributed (that is, unless you're using a package like ...
- 43
35
votes
2
answers
41k
views
Why do I get zero variance of a random effect in my mixed model, despite some variation in the data?
We’ve run a mixed effects logistic regression using the following syntax;
...
- 571
4
votes
0
answers
2k
views
Fitting GLMMs for binomial data produces Error and Warning messages when using different fitting procedures in R.
I am trying to fit GLMM's to my data using the glmer function available in R's lme4 package. The data is available under the name block1and2 at: https://onedrive.live.com/redir?resid=1B727FC7180E87DF%...
1
vote
1
answer
8k
views
R lme4 1.1-7: REML=FALSE giving error "extra argument(s) ‘REML’ disregarded "
I'm trying to fit a model with the function glmer (lmer4 1.1-7 package) in R using REML but I just get an error saying ...
- 135
0
votes
1
answer
5k
views
Linear mixed effect models with two independent variables
I am estimating a random intercept and a random slope model using the following R code. My dependent and independent variable are both continuous.
...
- 163
1
vote
0
answers
161
views
R-squared for linear mixed effects model [duplicate]
I ran linear mixed effects model in R.
model<-lmer(yld ~ rain + (1+rain|state),data=data,REML=FALSE)
Is there any way I can generate an R-squared for the ...
- 163
0
votes
0
answers
6k
views
Q: plot glmm fixed and random effects (glmer in package lme4) using ggplot2
I am trying to visualize the results from a glmm that I ran with the lme4 package.
...
1
vote
1
answer
1k
views
Significance of the overall model GLMM using lme4
Maybe it's a basic question, but I'm learning about GLMM using the lme4 package. I'm confused about the way that I can know the significance the overall model using glmer.
First, the random model is:
...
- 165
2
votes
2
answers
5k
views
Coefficients from glmer in R
In a mixed effect model where the intercept is random effect and the slope is fixed effect (see the code below), I understand the output of summary(glmer(...)). But ...
- 1,704
0
votes
0
answers
1k
views
Calculating random effects from a glmerMod object (r package lme4)
Using the lme4 package, how does ranef() calculate (or extract) estimates of random effects from a ...
- 395
7
votes
1
answer
1k
views
GLMM and two slopes
My outcome variable is binomial, and I have 11 independent variables and a time variable. The time variable has different slopes, so I fixed it to time-before and <...
8
votes
1
answer
12k
views
Interactions between random effects
I'm considering a mixed-effects model to try to understand factors that influence the number of ticks sampled on wild rodents. My data is nested so that I have one tick count per rodent, multiple ...
- 103
1
vote
0
answers
430
views
Lme4 Error Help: "maxstephalfit...pwrssUpdate"
I am using a mixed model to assess the effects of various treatments on bee behavior (e.g., avoidance frequency - total avoidances per total visits; feeding frequency, and mating frequency). Bee ...
- 11
0
votes
1
answer
172
views
Should I be using a GLMM?
I'm looking at the influence of pollen type on whether a flower sets fruit (i.e., yes or no = 1 or 0). Then looking at number of seeds per fruit (1-6 possible).
I was told I should use lmer, however ...
- 1
1
vote
0
answers
598
views
plot effects on glmer
I done a GLMM with the function glmer from lme4, the variable paternity is binomial (yes or no)(...
- 11
5
votes
1
answer
3k
views
Binomial GLMM: Model validation & ceiling effect
My data has a binary response acc(correct/incorrect), one continuous predictor score, three categorical predictors (...
- 313
19
votes
1
answer
7k
views
Meaning of a convergence warning in glmer
I am using the glmer function from the lme4 package in R, and I'm using the bobyqa optimizer ...
- 904
24
votes
2
answers
26k
views
How to apply binomial GLMM (glmer) to percentages rather than yes-no counts?
I have a repeated-measures experiment where the dependent variable is a percentage, and I have multiple factors as independent variables. I'd like to use glmer from ...
- 1,384
0
votes
1
answer
450
views
Null GLMM Poisson underestimate the mean of the response variable. Is it indicative of poor fitting?
I want to test the fixed and random effects of some covariates on a discrete variable with non negative values. In exploratory analysis I fitted a null Poisson GLM and an null Poisson GLMM. However, ...
- 3
4
votes
1
answer
5k
views
Level-2 predictions with lme4/glmer model
Let's say I've fitted a 2 level model with glmer like this:
...
- 205
3
votes
1
answer
14k
views
Mixed effects model validation and selection with `lme4::glmer`
If I had a glm using on count data I may do the following:
glm(response ~ exp1 * exp2, family = poisson, data =data)
The ...
- 1,007
4
votes
1
answer
1k
views
7
votes
1
answer
2k
views
How to calculate estimated proportions and their confidence intervals from a mixed model?
I have an experiment with two treatments. It is a split plot experiment, with the structure Block/Treatment1/Treatment2. Each treatment has 2 levels. The dependent variable is presence/absence data ...
- 1,257
22
votes
5
answers
25k
views
How to assess the fit of a binomial GLMM fitted with lme4 (> 1.0)?
I have a GLMM with a binomial distribution and a logit link function and I have the feeling that an important aspect of the data is not well represented in the model.
To test this, I would like to ...
- 14.4k
3
votes
0
answers
464
views
Plotting fit for binomial lme
I've been asked by a reviewer on a manuscript to provide plots of a model fit for a binomial lme which is specified as follows:
...
- 73
7
votes
1
answer
8k
views
Weights argument in glmer() when predicting proportion data: why is it needed when all weights are around the same?
What do the weights argument in glmer refer to? I used sample sizes as weights with ...
- 783
9
votes
1
answer
13k
views
How to account for repeated measures in glmer?
My design is as follows.
$y$ is Bernoulli response
$x_1$ is a continuous variable
$x_2$ is a categorical (factor) variable with two levels
The experiment is completely within subjects. That is, ...
- 101
3
votes
1
answer
8k
views
Order of nested random effects in lme4
I just fit a model in lme4, and I'm wondering what the heck I fit...
I have individuals id, and each is measured pass/fail on items that can be described using two ...
- 4,912
14
votes
1
answer
16k
views
Calculating ICC for random-effects logistic regression
I'm running a logistic regression model in the form:
lmer(response~1+(1|site), family=binomial, REML = FALSE)
Normally I would calculate the ICC from the ...
- 175
2
votes
0
answers
704
views
Overfitting in GLMM
I have fit a mixed model with lmer() and am left with 4 significant interaction terms.
There were found by removing the interaction term and comparing with the ...
- 1,193
12
votes
2
answers
23k
views
How to test for overdispersion in Poisson GLMM with lmer() in R?
I have the following model:
> model1<-lmer(aph.remain~sMFS1+sAG1+sSHDI1+sbare+season+crop
+(1|landscape),family=poisson)
...and this is the summary ...
- 711
4
votes
0
answers
920
views
Mixed-effect modeling with paired observations & bounded response variables
I am quite new in the field of mixed-effect modeling. For a beginner like me, I guess I combine several levels of complication in my analysis: paired observations & bounded response variables. I ...
- 61
47
votes
2
answers
77k
views
How can I test whether a random effect is significant?
I am trying to understand when to use a random effect and when it is unnecessary. Ive been told a rule of thumb is if you have 4 or more groups/individuals which I do (15 individual moose). Some of ...
- 1,219
1
vote
2
answers
1k
views
Can I run a GLMM model when I have one observation for most subjects?
I have a binary DV and my panel data set contains more than one observation
for only 20% of the subjects which makes it very unbalanced.
Is there anything methodologically wrong with doing a mixed ...
- 141
8
votes
1
answer
1k
views
How close to zero should the sum of the random effects be in GLMM (with lme4)
I'm using the lme4 package in R to do some logistic mixed-effects modeling.
My understanding was that sum of each random effects should be zero.
When I make toy ...
- 239
2
votes
0
answers
2k
views
How to construct GLMM model for repeated measures with binary responses with lmer
In my experiment I assigned subjects to one of the 3 treatments A, B or C. Within each treatment, a single subject was tested with two models sequentially. The test sequence was randomized. The ...
- 21
4
votes
2
answers
256
views
How to compare whether the odds of success of different levels of a predictor are different from 0
I hope I am able to word my question clearly. Suppose I have a model below:
glmer(Y~X + (1|subject), family="binomial", data=dat)
The intercept is the log odds ...
- 467
3
votes
0
answers
1k
views
Analyzing split-plot design in lme4 in R
I have the data from a split-plot design where A is my whole plot fixed factor with two levels and B is my subplot fixed factor with 2 levels and C is my random block factor. How do I analyse these ...
- 31
0
votes
2
answers
2k
views
Binomial GLMM not converging / Random effects variance and stdev = 1 resulting in AIC = Inf
I am using a binomial GLMM to assess differential habitat selection between two species with model selection using AIC.
When I use many variables (8), the models converge but are not significant. ...
- 73
19
votes
2
answers
15k
views
Random effect equal to 0 in generalized linear mixed model [duplicate]
Sorry if I'm missing something very obvious here but I am new to mixed effect modelling.
I am trying to model a binomial presence/absence response as a function of percentages of habitat within the ...
- 191
3
votes
0
answers
482
views
Binary interaction terms using lmer
I am trying to create a model using the lmer function. The model will contain the continuous response term "Average.profit" and explanatory terms "Type", "OtherType,...
- 1,193
5
votes
1
answer
3k
views
Diagnostic plots for lmer
I am trying to produce a glmm using the lme4 package in R. To validate my model I would like to produce some diagnostic plots ...
- 1,193