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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16 views
random effect variance as pseudo-rsquared in GLMM
Suppose I have data on the abundance of a species across multiple sites that differ in some covariate of interest. Suppose that the logarithm of the abundance (logAbun) meets assumptions for linear ...
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1answer
28 views
Using variance-covariance matrix of mixed-effects logistic regression to obtain p-values for custom contrasts
My question is a follow-up to this question, following through on @Isabelle Ghement's excellent series of responses. I just want to run this past some people in the know to see if what I am doing is ...
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8 views
R glmmadmb continuous vs categorical interaction multiple comparisons
I'm running a model using glmmadmb and I'm not sure how to do multiple comparisons on an interaction between categorical and continuous predictors.
Here are details on the model and data:
My ...
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1answer
70 views
Computation and interpretation of marginal effects in a GLMM
I am currently working on a GLMM model which uses a Poisson distribution and need to compute and interpret marginal effects from this model.
The model outcome consists of a count (COUNT) collected ...
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9 views
Adjusting range of predicted values in ggeffects [migrated]
I am using ggpredict to plot the marginal effects of temperature (a continuous variable) from a glmm zero-inflated model:
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25 views
incorporating temporal autocorrelation into GLMM
I am examining the relationship between presence at a site over time, and I am interested in determining if there is a decline in presence as an individual gets closer to their final departure.
Due ...
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1answer
14 views
How to interpret effects of predictors with large confidence intervals in GLMM?
(This question is somehow related to my previous one)
My aim is to find out about which effect several predictors have on my response variable, I am interested in the direction and magnitude of the ...
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0answers
16 views
Distribution/analysis method for small dataset with many small/zero values
I have a relatively small dataset (160 observations), of which a very large number of values for response variables are zero or very small (e.g., 114/160 values are 0; range 0-4250, with only 11 ...
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1answer
113 views
Which random effects to include in this GLMM?
In my study growth of plants was measured in different years on different plots (all plants were measured in all years).
The question I'd like to answer with my model is: Which factors influence ...
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54 views
Covariance structures in glmmTMB for temporal autocorrelation
I'm running a zero-inflated, mixed-effects negative binomial model with the glmmTMB package in R.
My current format:
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1answer
17 views
Differences between sexes across months with repeated IDs
I'm trying to figure out the best way to analyze the difference between sexes and across months for the means of a specific behavior (most individuals measured have repeated measures across the 5 ...
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1answer
45 views
Interpretation of fixed effect coefficients from GLMs and GLMMs
I am currently interpreting some glm's and glmm's based on distributions with log link functions (gaussian - log, and negative binomial) and have started going in a bit of a loop regarding the ...
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1answer
63 views
Linear mixed effects model with time series
I have been reading through the different posts here on linear mixed effects models, but am still very unsure whether I have understood the task correctly, therefor I am reaching out for help by the ...
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21 views
Underperforming participants (<50% accuracy) in LMM
I have to perform a linear mixed model analysis on behavioural conflict paradigm data (ie analysis of congruency effects) and I'm struggling to find reliable sources on what to do with respect to ...
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1answer
42 views
Mixed-effects Generalised Linear Model (GLMM) to detect significant differences in bird observation data
I am trying to analyse a set of bird count data associated with an environmental impact assessment I am running, but require experts to get this right. I am unsure how to formulate the model and ...
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0answers
22 views
Three way interactions for generalized linear mixed effects model and interpretation of post hoc comparisons
The data I am working on has three categorical variables and one continuous variable. I am using a generalized mixed effects model across four time points before and after administering a drug. The ...
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2answers
69 views
What are the assumptions of a Gamma GLM or GLMM for hypothesis testing?
What are the assumptions when doing hypothesis testing using a Gamma GLM or GLMM? Are the residuals suppose to be normally distributed and is heteroscedasticity a concern like the Gaussian (normal) ...
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0answers
71 views
Overdispersion parameter in R's glmmTMB
I am using R's glmmTMB for modeling negative binomial mixed effects. In the output, I see the following line : ...
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1answer
30 views
Which family to use for GLMM with 3-level categorical response variable in R?
I'm building a model with a 3-level categorical response variable and both fixed and random effects to analyze data from a survey of volunteers. My response variable ('wellbeing', self-reported) has ...
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14 views
Is the class probability in Classification models always the probability of Success
I have a Class variable with classes as ("Yes", "No").
In order to use that in the classification algorithm, I have converted that to factor as : factor(Column_name, levels = c("Yes", "No")).
Post ...
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1answer
37 views
Why do we get the same AIC for different models in a GLMM?
Our problem here described is to interprete the AIC from a GLMM negbin. Our data compose by 2 Categorical variables (Yes/Not), 2 Numerical variables and our random factor, all without any NA. We ...
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1answer
39 views
Zero-inflation GLMMs: On the use of different sets of explanatory variables in main and ZI formulas
my questions are general in nature so I won't provide any data.
For reference:
I am using the package glmmTMB in R so if my terminology is weird it is because it is a mix of this and other sources I'...
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1answer
41 views
Interpreting categorical interaction terms
I am wondering how to interpret results of interaction terms (see image below).
I think to know that the interaction term 1 (IV x potential moderator group 1) depicts the difference of association ...
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17 views
Analyse interaction/moderators first and then adjust for confounding
In my research I am interested in subgroup analyses.
I am looking at a general association between two variables (environment and health outcome) with interaction terms (personal factors, which are ...
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1answer
52 views
Is this an obvious situation for Generalized Estimating Equations?
Imagine collecting data in two locations at three points in time. The same 500 or so people are interviewed repeatedly, a year apart, in each place. There are many things being asked but of interest ...
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0answers
35 views
Interpretating `allEffects` and missing p-values
I need to run a logistic regression with random effects, about wheelchair users and hinderance due to environmental barriers:
...
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0answers
10 views
GLMM - Aleatory effects in R [closed]
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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1answer
114 views
Time Series of Wound Healing percentages / proportions
I am looking at wound healing over time and have hit a wall with analysis. My data consist of injury cases which are tracked over time. Injury healing is measured as percentage wound area/perimeter ...
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91 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
63 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
42 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 ...
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1answer
40 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
101 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
51 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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0answers
17 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
92 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
23 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 ...
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1answer
133 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
47 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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15 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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1answer
35 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
51 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
205 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
25 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
78 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
100 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
24 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
43 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
49 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) ...
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1answer
35 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 ...
