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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Multi-response MCMCglmm with random and fixed effects

I have many numerical variables with body measurements from animals from different populations and years (no repeated measures). With the total length of their bodies I calculated the residuals from ...
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Varying dispersion parameter (=dispformula) in glmmTMB in R to account for heteroscedasticity that originates from one predictor

I struggle with understanding the dispersion model and dispersion parameter of glmmTMB , and could not find answers anywhere. I constructed a GLMM using ...
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Can LMM or GLMM models handle negative values?

I am working on a set of correlated data. I am planning to apply LMM to my data, however my dependent variable has both positive and negative values. So, I was wondering if LMM or GLMM models can ...
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Binomial GLMM with proportions and categorical predictors

Study background My research question looks at the effect of age group (AgeGr) on gazing. Each infant was observed for 1h and signals with gazing (...
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How can I get p-values from a regularized GLMM?

I have a dataset containing information about patients in a hospital, with the following variables: Status for a certain disease (binary outcome) Hundreds of continuous biomarkers A few variables for ...
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GEE vs Marginal Models: Are they the same? How are they different?

In Agresti's "Foundations of Linear and Generalized Linear Models", section 9.1.3 unambiguously states that "GLMMs imply marginal models" and demonstrates in a few lines how "...
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On the prediction with mixed-effect models

I'm finding some struggles to understand the significance of the argument re.form in the function predict.merMod. In the ...
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How to deal with high correlation in a GLMM model in R

I would like to analyze the following GLMM model in R: ...
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Using lme4, empty model has a larger Condtional R2 than full model

I am interested in calculating the difference in conditional R2 between a full model and an empty one, but using the code below I get a higher conditional R2 from the empty model than the full one. ...
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Do guidelines pertaining to multicollinearity and overfitting in glmm pertain to population-level or subject-level data?

I've read guidelines when model building, such as to avoid overfitting keep at least a 10:1 ratio between the sample size of the lowest response variable class to the number explanatory variables, or ...
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In a GLMM, why does adding a main fixed effect change the significance of an interaction in the same model?

I am using a GLMM in SPSS to analyze the effects of spacing on learning. The main design has 2 within-subject conditions relating to how much time they had in between two learning sessions (ISI) and ...
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On the detection of the predictors responsible for the separation in logistic regression

I'm using multiple glmm models and I have separation and pseudo-separation situations. I want to know if there are any tools in R to extract the predictors ...
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Residual diagnostics for GLMM using Gamma distribution with identity link

I am using a two-level generalized linear mixed model (GLMM) with Gamma distribution and identity link. In terms of residual diagnostics, I understand that the following assumptions needs to be ...
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Validation, Interpretation and Post-hoc testing with a zero-truncated GLMM (using glmmTMB, DHARMa and emmeans)

I tried to go as far on my own as I could. But after 6 months of searching and reading, I'm still unsure if everything I did is statistically sound. Unfortunately, I neither have a statistican nor ...
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Similar estimate standard errors in GLMMs using a wide range of environmental variables

I have a data set on animal species diversity at 40 study sites from3 sub areas. The data comprise about 60 environmental variables. I am interested in the effect of each variable on the species ...
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How to analyze the data for measuring multiply site from same patients? Repeated Measures Analysis of Variance (ANOVA)?

I am doing a study to evaluate the effect of ossification ligament on thoracic vertebra. The purpose was to explore whether the evoked potentials is different between compressed area and uncompressed ...
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Scaling with categorical and continuous variables mixed model

I created I am working with data that has both categorical and continuous variables. The outcome variable y is a count. cat1 and ...
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I need help to choose between GLM and LMM or GLMM

I have a dataset of 200 subjects, who were divided into a control arm and a treatment arm (100 per arm). I am investigating the incidence of pain above a certain threshold, so i was thinking if using ...
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zero-inflated right skewed data - cpglm output

So I have a right skewed zero inflated dependent variable and I wish to run a model with that. It corresponds to a value of association between two words (so if 0 words are not associated). and I want ...
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Interpretation of GLMM summary in R [closed]

I have serious difficulty understanding the default R-summary of a GLMM model from the lme4 package. First of all, I would like to know how to interpret the ...
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Can a generalized linear model OR GLMM be used to address the hypothesis here?

Context I am trying to assist on a project where the goal is to compare the predictive validity of various regression approaches. I was originally drafted in to help on the basis I had experience ...
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5-fold CV to test predictive performance of glmm model with unequal sample size within groups

I am attempting to use 4-fold CV in order to test the predictive performance of a binomial glmm. In my data I have unequal sample sizes between the groups used as the random effect (18 of the 42 ...
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How does lme4 calculate residual variance for an LMM?

How does the lmer() function calculate residual variance for an LMM? If I code a model and then try to manually calculate residuals, the variance of the manually ...
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GLMMs with no intercept to test means of factor levels against zero

I want to analyse binomial accuracy data generated under four different conditions with a binomial generalized linear mixed-effects model using the lme4 package in ...
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How to construct GLMM with differing random effect variance structure by group?

I have a longitudinal dataset with a normally distributed outcome variable, a normally distributed predictor variable, and a binary grouping variable. I am trying to construct a GLMM with differing ...
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Interpreting a generalised linear mixed model and missing values. Plus what dose the Intercept say?

I am working on my data and i have 3 bordering element types, 4 distances and 18 different LS (locations). I would like to do a GLMM, with bordering element types + distance and their interaction with ...
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Issues with using GLMM to fit binomial dataset with sites nested within sub-watershed nested within larger watersheds

I am looking to fit a glmm for a project dealing with the presence and absence of a species of fish. I have been reading up on mixed modeling with hierarchical nesting and thought I had a decent grasp ...
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generalized linear mixed effects model mathematical equation

I am fairly new at statistics and I am faced with a problem of not understanding what it means and how would it look like in R script. Can somebody explane it to me? We use a generalized linear mixed ...
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How to control for a variable (gender of participants) in GLMM?

I recently tested some participants on a navigation task. The success rate in the navigation task is a binomial record of pass (1) and fail (0). I assessed participants in different environmental ...
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Mixed models for paired data, soil samples, effect of fire on seed bank

I'm investigating the effects of fire on the seed bank. I have an design with six plots, where I collected soil samples before and after the fire. At the moment I'm looking for changes in the ...
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Including dispersion parameter in prediction

I have already posted this question on r-sig-mixed-models mailing list but I received no response. I am fitting a ziGamma model using glmmTMB to predict the ...
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Analyzing animal behavioural data in R Studio (GLMM) and struggling to understand how to set up the model

I'm trying to determine whether there was any differences in behaviour (count data, frequency per 30 minute observations, categorized into 5 categories [e.g., affiliative, agonistic, etc.]) of a ...
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On how to fit a GLMM for an index whose value ranges from 0 to 1

I have been trying to fit a generalized linear-mixed model (GLMM) to examine how the consistency of animal orientation is affected by two fixed effects A and B, together with their interaction. The ...
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Obtaining estimated probabilities and 95% confidence intervals from binomial GLMM

I have a dataset where I am testing whether, overall, individuals are more likely to mate (mating_response) with individuals of the same type rather than a different type . The response variable is ...
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How to evaluate overfitting in GLMMs usnig R

I am using glmmTMB in r to model count data. I use poison and negative binomial error distributions. If I add one more predictor to my models I end up having convergence problems. I would like to ...
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Model selection between LMM and GLMM

I'm investigating how the variable "heading" affects reaction time (rt). Here is a subset dataset of 5 participants as an example: ...
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60 views

How to remove inter-year variation from my assessment of seasonal varriation

I have a 30 year dataset of fish sampling. I know from previous analyses that there is a huge amount of variation between years in catch rates. What I would like to do is create a descriptive plot ...
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Why predicted values do not match the GLMM binomial model summary?

I am using a GLMM to determine if COVID-19 business closures affected rat activity in the city. The response variable is binomial (no activity/activity), measured in bait stations the council uses to ...
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Including matched variables in regression models

I've been trying to search in the literature to see whether it makes sense to adjust for the variables I used to create matched pairs. To give context, I have a population of schizophrenia patients ...
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Handling 0s in a generalized linear model---climate data

I am using a generalized linear mixed model for analyzing climate data and incidence of a disease variable. The data follows a gamma distribution. But I am getting the following error when I am ...
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51 views

How to interpret the random effect of a random slope model?

I designed an experiment to observe the shading effect in the distribution of 2 species of crabs through time. So basically I have 4 levels of shading (no shade, 20%, 50%, and 80%) with 7 ID to each (...
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GLMM with 1 predictor, still necessary to do Chi-Square with Anova in R e.g.?

I frequently use the Anova function in R to test if any predictors in a GLMM are significant. Is this necessary if I only have one predictor. Can I just use the significance of the predictor instead? ...
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Performing GLMM on community data with manyglm

I'm analysing some arthropod community data with generalised linear mixed models (GLMMs), using the manyglm function from the mvabund package. This data has arthropods sampled from multiple trees in ...
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How to include parameters from a variogram to account for spatial autocorrelation with a GLMM?

One of my supervisors told me to try to estimate the parameters from a variogram and use them as random effects in a GLMM to account for spatial autocorrelation, and I did not really get the point of ...
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What should i use lme or glm? (Biostatistics, diversity) [duplicate]

I am trying to work on the data of my master thesis. I have to create some model, but I am stuck due to my lack of knowledge in statistics (I am working on it). My data are 58 sample points each has ...
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Interpreting parameters of zero-inflation model with random intercept

I had previously asked if parameters of a Poisson model with a random intercept can be interpreted marginally or if it has to be conditional on the random effects. Based on the answer I received, they ...
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Why do the standardized residuals of a general linear mixed model using transformed data show a negative slope? [duplicate]

My data is no. of individuals of a certain age-class in a group, and it is right skewed. When I did a general linear mixed model with the number of individuals in a group as a dependent variable and a ...
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Is a GLMM applicable in a non-full factorial experimental design with two dependent fixed effects?

At the moment I plan the statistics for an upcoming experiment in Biology with two fixed effects whose effect on a fitness parameter of a parasite I would like to test. The two fixed effects are the ...
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Assessing treatment effect with GLMM logit-link

I am currently trying to assess whether integrated treatments (pesticide (Pest) or landscape modification (Veg)) had an effect on mite infestation rates of small rodents. The data is designed as a 5 ...
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Random effects are not centered in mixed effects logistic regression model

Random effects are usualy modelled as normally distributed with zero mean. Thus I would expect that the mean of the estimated random intercepts is close to zero. However, in my example this mean is ...

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