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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Binomial glmm with a categorical variable including zero cell [duplicate]

I am analyzing the data using generalized linear mixed-effect models (GLMM) using the lme4 software package (Version 1.1-30 in R; Bates, Maechler, Bolker, & Walker, 2022). The model includes 2 ...
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How is AR(1) autocorrelation defined in a glmmTMB generalised linear model?

How is AR(1) autocorrelation defined / parameterised when using a R {glmmTMB} GLM? I have read through Kristensen and McGillycuddy's vignette (https://cran.r-...
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Testing and training data for LMM/GLMM

I was reading this article on logistic regression and ML and noticed that they explicitly mention the need for using training sets of data and testing sets of data: However, I have never seen this ...
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GLMM - are there pitfalls for modeling the error distribution independently of the variable relations?

I was running a LMM with random intercepts, as such: model1 = lmer(web ~ rain + body_size + placement + canopy + understory + (1|species)) To me the residual ...
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Logistic GLM vs GLMM diagnostic issues

Problem I am running through the diagnostics of two logistic regressions and two equivalent GLMMs with their only differences being crossed random effects (intercepts only). The output for the ...
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gamma distribution GLMM with negative values

Following this post: If using Glmm with Gamma distribution do i need to transform my data to be between 0 and 1?, I would like to know what the concensus is regarding modelling a response variable ...
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How should I introduce an OFFSET term for a BINOMIAL response variable?

I have a binomial response variable -proportion of removed fruits, or plant visited or not visited by a frugivore- in a GLMM. I would like to control for differences in the sampling effort (time) ...
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What is the hat matrix and why is it inappropriate for GLMM standardized residuals?

When I run this code to plot standardized residuals for a standard logistic regression: ...
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How to test whether there is a significant (general) within group trend with data from many groups

I am having trouble identifying the correct statistical method for the following problem: I have data on a characteristic (e.g. body length) from several individuals per species, distributed in an ...
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Reason for the error in ANOVA: models were not all fitted to the same size of dataset [closed]

I have been running with this error for a long time and I have been failing to fix it. Does anyone have an idea? ...
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Mixed effects model for paired subjects in a complex design

I'm new to the mixed effects approach and I'm struggling to understand how to apply it to my relatively complicated experimental design given that all tutorials and articles I read are not directly ...
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Is the Hosmer-Lemeshow test appropriate for logistic GLMMs?

I have read a bit on the Hosmer-Lemeshow test as a goodness of fit measure in logistic regression, though I have read that it is quite flawed in terms of power, effects in choice of g, and issues with ...
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Can I fit a mixed effect model with only one explanatory variable? [closed]

I am trying to understand how age (years) affects hormone concentration. Individual ID is included as a random intercept as this is a repeated measurement. I would like to use a mixed effect model. ...
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Modeling Target Variable based on Days Since Last Engagement

I have a data frame of engagement data for different sites for every day like this: SITE_ID Date Engagement A Count Engagement B Count Target Variable 1 1/1/2022 0 0 1 1 1/2/2022 0 0 0 1 1/3/2022 ...
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What is Nakagawa repeatability measure quantifying?

I have been reading about repeatability estimation, and ICC and I am a little confused about how the quantity is being reported given its computation. From Stoffel et al 2017, repeatability, $R$, is ...
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Does a Heteroskedasticity and Autocorrelation Consistent Estimator for generalized linear (mixed/non-mixed) models exist?

Does a Heteroskedasticity and Autocorrelation Consistent Estimator for generalized linear models exist? That would make GEEs outdated unless no-free lunch theorem suggests otherwise. I am only aware ...
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Do we consider participants who seem to have "outlier" slope? and how can we define/detect such participants?

I am new to glmm models. I am modelling my data (i.e., reaction times) by using a glmm (lme4 package), where I have only categorical predictors. I want to test the effect of the interaction between ...
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Strange result with GLMM (binomial)

I'm analyzing some data, using GLMM and obtain very strange results. The data is of student passing a test, each group of students belong to a different school. So I analyzed the data using ...
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Continuous x Continuous Interactions in Logistic GLM and GLMMs

Lets say I want to run a logistic GLMM like so: ...
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GLMM with scaled variable: do I need to back-transform?

I am fitting a GLMM to powerline collision data for a bird species- using distance to seasonal water, habitat and the presence/absence of line markers as predictors. Incident is a binary response (50 ...
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DHARMa diagnostics: what to do with sig. KS test and quantile deviations

I am fitting a GLMM to powerline collision data for a bird species- using distance to seasonal water, habitat and the presence/absence of line markers as predictors. Incident is a binary response (50 ...
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Choosing between univariate GLMMs to assess inclusion in a multivariate model

I am currently doing a project on environmental determinants of malaria vector distributions. I'm using remote sensing data for environmental variables linked via GIS. I have run univariate (binomial) ...
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Random effects in Generalized Linear Mixed Models / alternative with Generalized Linear Models

I am trying to see if some anthropic variables (e.g., Population density, Population growth, and Roads) explain animals' distribution. My dependent variable is the percentage of area occupied (...
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Backwards model selection, model average and model prediction. I'm lost

I am trying to see whether two grouping variables and their interaction (let's call them B and C, where B has two levels and C has three levels) affect the behavior of an animal (described by A, a ...
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glmmTMB, zero inflation and response variable with values very close to 0 with a gamma distribution

I have 3 repeated values of a specific metabolites per person post vaccination and I am trying to see if there is a difference in between vaccine groups overtime. I am trying to fit a glmm model (...
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Should I specify priors to increase the effective sample size for multimembership MCMCglmm?

I am wanting to use a multimembership MCMCglmm with the following model ...
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Several single-species GLMMs -> A multi-species GLMM (random effects syntax?)

I'm looking to describe annual relative abundance for several species over several years by analyzing point count data. I'm using a Poisson GLMM in glmmTMB for each ...
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Interpret the output of a GLMM with binomial data

I am a biology student looking at the occurrence of a certain behaviour during breeding in an animal and which variables predict the occurrence of that behaviour. The behaviour was recorded as "...
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Computing power (1-beta) for GLMM in SPSS

How do I compute power (1-beta) for GLMM in SPSS? Thanks.
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calculating ICC manually versus the performance package

I reproduced an example I found on Stackexchange, here, and I failed to get the same ICC using the performance::icc package in R. My reproducible example is below. Can someone explain to me why the ...
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GLMM Outputs from LMER: Random Effect Variance does not reside within 95% CIs in log-transformed response variables

I have produced a mixed-effects model (lmer) that is analysing the difference in area between three protocols of growing mini-brains. I have takes into account various fixed effects including the type ...
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diference between nested and crossed random effects within my study [duplicate]

dear. How are you. There is long since I have been trying to solve a doubt about diference between nested and crossed random effects within my study. So I am here to ask and seek for some information. ...
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Help in interpreting glmer and log (odds) as well as plotting my data

the statistical model I had to use for my data turned out way more complicated than I expected. I could really use some help interpreting the results. I am very grateful for any help/advice you have ...
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Which model should I use, when I have a mixed Design (3 between x 2 within), but only 1 measure for each of the within-subject levels?

I want to collect experimental data with 3 between subject levels and 2 within-subject levels to observe main effects as well as interaction effects on a binomial outcome. I had firstly defined the ...
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Linear mixed model: Is subject-specific random effect for interaction meaningful if one factor is varied between-subjects?

I plan to apply a within-subjects design. However, currently, I am investigating my pilot data in which a between-subjects design was applied. The planned model comprises a subject-specific random ...
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Relationship between log-linear (e.g. Poisson) GLM and GLMM with random intercepts

In their textbook "Analysis of Longitudinal data" Diggle et al. state (p. 137 in the second edition) that: In log-linear models for counted data, random effects and marginal parameters can ...
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How to make predictions from a GLMM model where the prediction space has fewer independent variables than were used to generate the model?

THE PROBLEM I have a Generalized Linear Mixed Effects (GLMM) model that is relating counts of an organism to relevant environmental covariates. Once this model is generated, I intend to apply it to ...
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Are these effects missing from my glm output because of a possible dummy trap?

I have a few generalized linear mixed model questions. I have an experiment that asked "is there a differential response between asexuals and sexuals by population density?". I am ...
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What is an alternative to Chi-Square for observed vs. expected variance suitable for repeated measures?

I want to test for individual-level side preference of a behaviour during an experiment, and found a way to do this using a chi-square test that uses the number of right (or left) turns out of the ten ...
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How to fit a GLMM with non-negative non-integer continuous data?

I am trying to analyse a data set which has numbers of behaviours performed under 2 different predictor variables. The numbers of behaviours were standardised to rates per minute, since the ...
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goodness of fit test for model

I did GLMM with negative binomial family. After checking goodness of fit using the equation "1-pchisq(summary(model4)$deviance,summary(model4)$df.residual)" it gives the value zero. what it ...
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How to validate the effect of the type of Task on participants' performance using count data

We conducted a user testing with two groups of participants (Group_A, Group_B). Group_A performed Task_A (a writing) under Condition_A. Group_B performed Task_B (a writing) under Condition_B. Group_A ...
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If I analyse the pre-post data, should the "pre" (time=0) be included or excluded from the reponse?

Let's assume I analyse repeated data, recorded at t0, t1...t3. I want to analyse the response itself and then check various contrasts, for example change from baseline or consecutive. If the model is: ...
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DHARMa problems: Poisson or Zero-inflated negative binomial model?

I have a dataset of abundance of of rodent (AA) in 63 sites, which located in two main area (northern and southern part, NS). AA ...
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Random effect with compound symmetric covariance structure in glmmTMB

I have a dataset of abundance of a kind of rodents(AA) in 63 sites, and want to know which environmental factors can explain the rodent abundance, and because the sampling sites are basically locate ...
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What is the difference between robustlmm and clubsandwich in R?

Excuse my ignorance, I am trying to get around a problem with my statistics that involves severe outliers issues, with heteroskeskedacity. My model using linear mixed models, in R, with repeated ...
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How to understand the following linear mixed model?

I wonder how to understand the following mixed effect model. $$y_{ij}|b_i \sim N(\mu+b_i+\beta_j,\sigma^2), \ \text{where} \ b_i \sim N(0,\sigma_b^2)$$ for $i=1,2,....,M, \ j=1,2,...,N$ What is the ...
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How to estimate/simulate sample size based on glmm?

I would like to estimate the minimum required sample size in R to detect an effect size I found in a recent study. The simulation should be based on an already calculated mixed effects glmm with a ...
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Nested random effects for testing individual choices when choices are made in a group

I'm planning an experiment where individuals' choices will be measured. I want to test individuals' choices before and after an intervention. The problem is the individuals are in groups and cannot be ...
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Basic GLMM model fitting

I'm fairly new to fitting GLMMs but hoping I can get some advice. I have run an experiment where participants in an intervention and control group each perform a task (A) and then perform a similar ...
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