Questions tagged [glmm]
Generalized Linear Mixed (effects) Models are typically used for modeling non-independent non-normal data (eg, longitudinal binary data).
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GLMM - Aleatory effects in R [on hold]
I have a question if you could help me?
I studied during 2 days (48 hours), 8 times per day (every 3 hours), 3 nests per species (2 species), the number of ants every 3 min that walk by a point. I ...
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0answers
82 views
Mixed-effects logistic regression
I'm new to data analysis and I'm trying to perform a mixed-effect logistic regression.
My data look like this:
...
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1answer
53 views
Can I used a General Linear Mixed Model when there are repeated observations for only a small proportion of cases?
I am trying to make a model with a response variable of performance on a test (interval data), along with predictors for test performance. It's a threshold test, so anyone that passes it will not have ...
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1answer
26 views
Grand-mean centering in GLMM changes estimates for variance (and everything else)?
I know that when running a linear mixed effects model, centering around the grand mean should change the estimates for the coefficients, but not the estimate for the variance.
For example, I have ...
2
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1answer
24 views
Surprisingly large difference between conditional and marginal effects estimates
I am performing a logistic mixed effects regression on some data I have. There are 201 participants answering a question over 6 time points. The model includes 4 fixed effects: X1, X2, X3, and Time. ...
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0answers
83 views
Time series models (e.g. ARMA) a type or extension of GLM? Particular/stipulated forms of dependence in time series models
I am trying to understand the relationship between ARMA Time Series models and the GLM (Generalized Linear Model) family of models. As far I know, all GLMs have the following 3 components: 1) random ...
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1answer
25 views
Calculating 95% confidence intervals for GLMM additive coefficient - count data estimates
I am running a GLMM on some data where the response is count data, using the glmmADMD package in R. I would like to plot the results giving estimates for the response variable with certain explanatory ...
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14 views
Testing equality of estimates in MCMC GLMM
I am estimating a Poisson mixed model using MCMC via the MCMCglmm package in R. My dependent variable is repeated measures of event counts in each of several ...
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0answers
33 views
Model convergence problem; non-positive-definite Hessian matrix with glmmTMB in R
I'm trying to fit a GLMM using the package glmmTMB in R. The model has a negative binomial distribution. The fixed effect "Treatment" has two levels (low or high), "Sampling" is the number of ...
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1answer
21 views
Support for modelling random effects first?
Regarding linear mixed models, I am looking for a reference that advocates first determining the appropriate structure of random effects (by first modelling only random effects), and then ...
3
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1answer
61 views
Calculating confidence intervals of marginal means in linear mixed models
I'm using different R packages (effects, ggeffects, emmeans, ...
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1answer
39 views
Can you perform a likelihood ratio test on two linear mixed effects models with different optimizers in lme4?
I ran into an error with my full (but not simple/null) model, so I had to use a different optimizer to avoid the fitting problems. Can I still do an LRT test using those models?
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9 views
GLMM with rare events causing issues with specificity?
I have run a generalized linear mixed model (link=logit) and my outcome of interest is present in about 8% of observations. The total sample is 1,717,323 and of these 131,389 observations are where ...
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0answers
22 views
Using GLMM to explain vegetation change as a function of change in soil parameters
I have a dataset that consists of vegetation datasets (species/abundancy tables) and soil parameters (tested for ten parameters per soil core). Three different rounds of these data are recorded in ...
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1answer
45 views
Calculating Log-Likelihood of Logistic Adaptive-Quadrature GLMM for Comparison with Fixed Model
Fitting a binary logistic GLMM here, with ungrouped data (all responses either 0 or 1).
It says in this thread and in the documentation of anova.merMod that the ...
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4answers
176 views
Is it mandatory to subset your data to validate a model?
I'm having a hard time getting on the same page as my supervisor when it comes to validating my model. I have analyzed the residues (observed against the fitted values) and I used this as an argument ...
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0answers
20 views
How to best evaluate a cross validation of a logistic regression using cbind
I ran a logistic GLMM using cbind for the response:
...
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2answers
53 views
GLMM species count data with transects
I am trying to create a GLMM model which explains differences in abundance/count of three species of scorpion around a field reserve in different forest types.
-I have 7 trails in different forest ...
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2answers
82 views
glmer fitting different models if binary variable is integer 0,1 or factor
This seems like a relatively basic question, but I can't find good pointers after two days of searching.
I am trying to fit a generalized linear mixed model to data obtained in an experiment. The ...
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0answers
22 views
GLMM with many and highly correlated features
Lately I came upon a very interesting project, which also made me thinking since it was the first time for me to work on such data.
So, I have 2-level data, with 60 participants having 2-3 ...
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0answers
26 views
glm model with two nested variables in R (lme4)
I have a problem writing a glmm model in the lme4 package. A little background: I measured olfactory behavior (OB) in fruit flies (80 genetic lines in total), they are from two different populations, ...
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1answer
45 views
Regression with frequency rating in percent as dv
I seem to have a similar issue as asked in this thread, nevertheless I'm still clueless about what model I have to fit to my data.
I conducted a repeated measure experiment (consisting of 2 sessions) ...
0
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1answer
28 views
Model validity and specific contrasts in mixed model
I have a design where mice are distributed in a two-way anova setup. With genotype (WT and KO) and treatment (Ctrl and Treat). From each mouse 5 different tissues have been extracted and the number of ...
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0answers
20 views
How to assess two random effects and interpret
I want to study the impact of two numerical factors (A & B) on outcome C (binomial). I used glmer in lmer4 package, and my models were as
1) m1<-glmer(C ~ A+B+(1|subject)+(A+B-1|subject), ...
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0answers
25 views
Detecting over-parameterization in GLMM: number of observations to number of parameters ratio?
I'm using generalized linear mixed models (GLMM) to model the effect of several testing conditions on the binary outcome of a behavioral trial. There were 40 individual subjects in my experiment, and ...
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0answers
55 views
Why are conditional and marginal pseudo R^2 the same in this example?
Here is a reproducible example:
The problem is that when I calculate Pseudo R^squared for the null model it gives 0.18 to conditional R^2, the variance explained by the random factor is not 0. However ...
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1answer
25 views
How do I estimate the mean of groups as well as subgroups within a group?
For example,
I have three groups A, B, and C. A has two subgroups, A1 and A2. B and C don't have subgroups. I have multiple observations for each individual in these groups. I want to estimate the ...
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1answer
37 views
Random effects specification in modeling panel (longitudinal) data
I am fitting a negative binomial model with mixed effects on a dataset with repeated measures in time. Each observation is a province-year combination, meaning province 1 year 1, province 1 year 2, ......
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1answer
29 views
How can we calculate AIC from a negative binomial GLMM?
Our problem here described is to calculate AIC from a GLMM negbin.
Our data compose by 2 Categorical variables (Yes/Not), 3 Numerical variables and our random factor, all without any NA.
We want to ...
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1answer
42 views
lmer logit regression - unexpected coefficients
I have a simulated dataset of N observations over NGroup individuals with a covariate x1 and ...
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0answers
10 views
Repeated measures on subjects without all subjects present in each period
I am working on a dataset in which several individuals were observed over several periods. However not all individuals were observed at each period. Due to repeated measures on individuals I have to ...
5
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2answers
190 views
GLMM for count data using square root link in lme4
I have data from a field survey. The objective of the study is to relate number of seedling (respond variable, count data), landform (exploratory variable, categorical variable with 3 levels) and ...
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1answer
37 views
Scale and log10()?
I'm trying to create a mixed model and I've both scaled and logged (log10) some of the explanatory variables. Residuals of the model are looking good. I was wondering whether there are any issues ...
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1answer
37 views
Linear mixed effect models - Why is time specific variance under estimated?
Suppose you fit a linear mixed effect model
$$y_{ij} = \mu + \beta^T x_{ij} + u_i + \epsilon_{ij}$$
where $u_i \sim N(0,\sigma^2)$ and $\epsilon_{ij} \sim N(0,\nu^2)$.
I have noticed that when ...
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2answers
76 views
Beta regression estimates and confidence intervals on response scale
I'm using GLMMadmb for my beta regression. I'm having a bit of trouble. I understand beta regression uses the logit link function and I know how to get from logits to probability. Here's selected ...
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1answer
192 views
How do you deal with “nested” variables in a regression model?
Consider a statistical problem where you have a response variable that you want to describe conditional on an explanatory ...
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1answer
158 views
R glm() with a categorical response variable [duplicate]
I want to know whether I can use glm() with a categorical response variable, and if yes how exactly.
I have a response variable with three unordered levels, and both categorical and continuous ...
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1answer
30 views
Specify nested random effects [closed]
I have data from a field survey. The objective of the study is to relate number of seedling (respond variable, count data), flood duration (exploratory variable, categorical variable with 3 levels) ...
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0answers
20 views
Different significance in GLMM interactions
I am confused about different significance results obtained in GLMM's.
First, my set of relevant variables:
...
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1answer
96 views
GLMM optimiser test - optimx.L-BFGS-B doesn't converge, but the rest do
I am running GLMM using lme4 in R for the first time. I have a complex model (with three main effects and four interactions), as well as a random intercept of ...
2
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1answer
45 views
Is Repeated Measures ANOVA appropriate for flower production over time?
I wanted to check here to see if a repeated measures ANOVA would be a good option to analyze my data, or if you have any other suggestions? I have read that GLMM is another option for time series data,...
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0answers
64 views
Which method to use when calculating the confidence interval of GLMM Gamma Regression with the lme4 package in R
I am fitting a GLMM with family gamma using the lme4 package in R. Below is a code example to simulate the gamma GLMM fitting.
...
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1answer
32 views
Equation for GLMM w crossed random effects and logit link function
I am working on a GLMM model with crossed random effects and I would like to write an equation from the output where the outcome is the probability rather than a log of the odds.
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0answers
59 views
How to do classification in mixed effect models in python. My data is nested into groups with binary outcome
Lets say I have 10 sellers (S1-S10). Each seller has 7 buyers which are different for each seller (B1-B7 for S1, B11-B17 for S2 and so on). Each Seller buyer combination has a product category (P1, P2....
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1answer
22 views
Why does PQL vs MCMLEs optimisation give wildly different variance estimates?
In order to better understand modelling GLMM's using R I decided to re-do the example given in this Introduction to GLMM Package using the salamander dataset (provided in the glmm package).
The ...
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2answers
129 views
Using glmm() to fit a model with repeated measurements?
I want to fit a GLMM model using the glmm() function in R. Its documentation is given here. I'm struggling to understand how to fit it given the way it's described in the documentation. Specifically, ...
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1answer
30 views
Intraclass Correlation Coefficient with Bayesian ordered-logit GLMM (STAN)
I am fitting a Generalized Linear Mixed Model for an ordered outcome, in form of an ordered logit, with random intercept and slope. For this task, I am going Bayesian by handling STAN through the ...
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0answers
18 views
glmer: distribution law for number of events / time
Sorry if this is a basic question but I can't find an answer that is clear enough, so I prefer to ask.
I want to model a number of events (number of gaze) that depends on the behaviour that one ...
5
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2answers
120 views
To choose between linear or generalised mixed effects model, what is the most important thing to consider?
Linear mixed effects models are for continuous variables.
Generalised ones are for non continuous, e.g., binomial.
We have a task in which subjects can get each item correct or incorrect. I'd say ...
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1answer
40 views
How to interpret a linear mixed model formula
In this model:
Biomass ~ Species + (1|Site / Species)
Biomass and Species are continuous variables, and ...
