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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Is there a model that can handled unbalanced repeated measures data with 1 OR 2 follow ups?

I want to identify predictors of a binary healthcare outcome in a purely observational study, and some of my participants have 1 recorded outcome timepoint, while others have 2 recorded outcome ...
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How can I calculate standardized weighted residuals 2 for a beta family glmm in R?

Hello and thank you for your time! I’m trying to calculate the "sweighted2" residuals for a beta family glmm with varying dispersion (aka precision parameter aka phi) fit using glmmTMB in R. ...
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How do I interpret this hurdle model summary (pscl)?

A little bit about my data: I have four treatment groups: control, early, late, both. For each group, I counted nymphs and eggs on leaves on five different dates. The design is randomized complete ...
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What is the best way to deal with over-dispersion in a poisson GLMM?

I am currently in the process of trying to complete a poisson GLMM analysis with two fixed (with an interaction) and two random effects using the glmer() function of the lme4 package. Using the ...
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How come a Poisson GLMM predicts a higher overdispersion than in the observed data?

I am using package brms in R to fit a Bayesian generalized linear mixed model in which: the response variable is the count of a phenotypic structure (e.g., toes) ...
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Doubts about a glm [closed]

I'm running this model on R: modelogeral<-lmer(lognplanta~Clas_renda*sexo*idade*ocupacao*escolaridade*Clas_npessoas*(1|comunidade),data=bruno) When I run the ...
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Dispersion parameter of exponential family (phi) in glmer

I need to extract of a glmer adjust the dispersion parameter (phi) for Gamma and Inverse Gaussian. I know the relation phi=1/sigma^2, however, the glmer summary gives a different sigma: "sigma: ...
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Correct distribution to model proportion of time in a day

I would like to determine how the presence of researchers influenced the amount of time that shorebirds spent on the nest in a day. My data consists of proportions that range from 0.715-0.997, which ...
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GLMM hurdle model for continuous data -Truncated negative binomial family in glmmTMB?

I am running a hurdle model using the glmmTMB function. My dependent variable is continuous and >= 0. I was looking for a function that would allow me to model the binary response in a logistic ...
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MASS::glmmPQL diagnostic

I am fitting models with MASS::glmmPQL of the form ...
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Convergence issue for GLMM

I analyzed reaction time data using GLMM. In order to find the best model based on random effect via model comparison, I incrementally added the random intercept and random slope of four factors (and ...
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How to interpret GLMM results?

My question is related with my previous post Extract variance of the fixed effect in a glmm. However, in this case I change the model that the GLMM follow. It follows a log family and as there are ...
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GLMM indicates a negative trend, graph shows a positive trend

I'm analyzing my data in R using a GLMM, of the format: glmer(y~x1+x2+x3+x4+(1|site),data=df,family=poisson) This produces a negative trend for variable x3. On the ...
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Generalised Linear Mixed Model Diagnostics using DHARMa

I am running a GLMM in R in lme4 package, the outcome variable is binary and the 10 fixed effects are a mix of categorical and continuous variables. The models have three random-effects. I am using ...
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41 views

mixed model variance-covariance matrix| parameter estimation

I am fairly new to LMM's and I am trying to undestand how the parameter estimation happens; According to this: Beta is obtained with equation 13.28. Beta is supposed to be the parameters for the ...
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60 views

Interpretation of binomial GLM (glmer) with interaction and results description

I would like to confirm if I am analysing the results of my model correctly and get some advise if I am missing something! I conducted the following model to analyse factors that describe the feeding ...
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Fitting Joint Model with GLMM

I'm looking to fit a joint survival model (example). For those who are unfamiliar, joint survival models are Cox proportional hazard models where the covariates are allowed to be time-varying and are ...
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How to select the family for a GLMM with non-normal, continuous data and lots of zeros

I'm new to using glmer's in the R package LME4. I want to run a repeated measures GLM for my data. The data is looking at a readout of an accelerometer and correlating to behaviour- so the readout has ...
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Why not always use generalized estimating equations (GEE) instead of linear mixed models?

I read about generalized estimating equations (GEE) here, here and at other sites. It is mentioned in first of above links that "the parameter estimates are nearly identical" for linear ...
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glmmLasso vs. lmmLasso vs. LMMEN to reduce highly correlated predictors?

I have trouble choosing the correct model and parameters for my problem. I have around 20 experts who rated the quality of brain tumor segmentations for around 20 patients on a 1 to 6 star scale. I ...
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GLMM - binomial

I am rather new to R. I am trying to run a GLMM - binomial logit. I have three independent variables (x1, x2, x3) and a dependent variable (...
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Leave random effects out when correlated with fixed effects?

Is it appropriate (or not) to leave a random intercept out of a model if the random intercept acts as a proxy for multiple fixed effects that are being included in the model? I have been given data on ...
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Interrupted time series using GLMM / GAMM: which time variables should be smoothed?

I have conducted a controlled interrupted time series analysis within a GLMM framework. I have run the analysis in both the control and treatment groups separately to quantify the basic effects: ...
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Extract variance of the fixed effect in a glmm

I would like to get the variation (variance component) in incidence (inc.) within each habitat while being mindful of random factors such as season and site This is my data set: Incidence: ...
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19 views

Plot the probability (success) of a binary variable from coefficients of a GLMM?

I have developed a GLMM (Mixed Generalized Linear Model), as you can see in more detail [here] (Is it correct to evaluate differences of a binary variable between different places with a GLMM?) ...
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42 views

Zero-inflated generalized Poisson mixed effect model with glmmTMB still zero inflated

I am trying to analyze a dataset using number of flowers as response variable and the interaction between two treatment variables (categorical with 2 and 3 levels) as covariates. I also have a random ...
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Interaction term alters degrees of freedom for main effects in glmmTMB model

I am using the glmmTMB package to test whether the probability of a seed remaining dormant in the soil (binary variable) depends on the population it comes from (fixed effect, 8 levels of population), ...
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mean event rate in negative binomial regression in R - using glmmTMB and emmeans

this is my first question here and am not a native speaker, so I'm quite nervous :) I'm analysing count data, where subjects are oberserved over a long period of time ( ca 3 years) and can have ...
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how to evaluate results with glmmPQL

First of all im thankfull for your attention. I have to evaluate the effect of 3 fixed effects in the vegetal coberture and i must use glmmPQL because my data has lineality condition problems and ...
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Which data visualization when running GLMM?

I'm analysing correct response rate and response time of participants on a task. For the first one, I ran a mixed effect logistic regression: ...
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1answer
32 views

GLMER Overdispersion and Error messages

I have a data set which involves 30 binomial absence/presences totalled for a ratio out of 1, which is the total score of a test out of 30 marks. The data requires fitting one of my predictor ...
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1answer
28 views

Interpretation of binomial GLMM with interaction fitted with glmer

I have a glmer model from the R package lme4 with a binomial distribution and I was wondering whether I am interpreting the ...
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DHARMa package diagnostic plots give different results

I am fitting a poisson GLMM of the type ...
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Converting LMM to GLMM

I've fit my model using lme (in nlme, R). However, this is not normally distributed. Taking the log of the outcome variable ...
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GLMERTREE with reponse in [0, 1] and multilevel design

I have multilevel data (with nested random effects: (1 | cluster-of-cluster/cluster) in lme4 syntax) where the response is a continuous variable between $[0, 1]$ (i....
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Set up and analyse planned contrasts in lmer() from lme4

I would like to analyse planned contrasts in my lmer() model from the lme4package. I have three factors: group (levels: trt, ...
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Modeling slope effects to measure individual consistency

I am trying to fit a model with some pretty sparse data; I cannot collect more data so please refrain from that suggestion. I do not have a large sample size, so I have issues with singularities for ...
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1answer
33 views

GLMM with ex-Gaussian distribution function (trial-level reaction time data)

I am trying to use GLMM in R to fit a mixed-effects model (three categorical predictors, one continuous predictor) to trial-level reaction times from a group of participants. The reaction time ...
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26 views

Standardize species richness by elevation

I am studying the effect of forest structure on recruitment. One of the variables is species richness defined as the number of species. The aim is to quantify the effect of species richness on ...
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How to provide error distribution from a GLMM?

I'm performing GLMMs in R Studio, but reviewers of my study asked me to provide the error distribution of those models. I've been reading other similar questions about this but I have not found what ...
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Questions about Random Effects in GLMMs

Someone reccomended me to use GLMM instead of GLM for the data I used for the manuscript. My data corresponds to transects in which I have counts of individuals of a species in several points along ...
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99 views

DHARMa diagnostics show significant deviations in KS tests for a glmm with beta distribution

I'm trying to use glmmTMB to fit a beta-distributed generalized mixed effects model with nested random effects. DHARMa residual diagnostics show a KS test with significant deviation. Is this serious ...
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1answer
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Intra-class correlation coefficient interpretation

I am getting a hard time to go around this and I am not sure my interpretation is correct. I have several models that look like this: change | trials ~ treatmentA + treatmentB + treatmentC + (1|...
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Can I discard parameters with a R-hat > 1.1 and consider the rest of parameters with a good R-hat value?

I have a binomial glmm model containing many regressors. When summarizing the estimates, some parameters show R-hat > 1.1, indicating chains have not mixed and estimates should not be trusted as ...
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68 views

Interaction-only model over full model: how to get interaction effects for all levels of a factor

I've looked for a question that could possibly cover this but I did not find any. It may be basic but as a R beginner I'm strugling with it. So here it is: I'm running a mixed effect model to test ...
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Next step after building GLMM logistic regresion: LRT, ANOVA?

I am a biologist in the middle of their PhD journey and I'm constantly learning new things about statistics but there are some things that are difficult for me to understand. Until now I had dealt ...
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23 views

P values from lmer with lmerTest - why REML= TRUE?

I would like to obtain p-values from my model fit with lmer()from the lme4 package. It looks something like this: ...
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11 views

Random effect in Phylogenic GLMMs from the species scientific names

I have a list of plant scientific names, all from a savanna-type ecosystem, including species authorities, with different attributes (measurements) for each plant. I need to implement sets of ...
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How continuous predictors are dealt within (G)LMMs' inference procedures (such as ML and REML)?

When considering (G)LMs (with no mixed effects), handling both continuous and categorical predictors seems pretty straightforward, as ML gives us an estimation for the parameters, $\beta_i$. However, ...

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