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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9 views

How to estimate the covariance matrix for outcome of logistic mixed-effects model

I have a logistic mixed-effects model below. $\mathbf{y}=(y_1, y_2, ..., y_n)^T$ is a n dimensions vector. $\mathbf{p}=(p_1,p_2, ...,p_n)^T$ is a n dimensions vector. $logit(\mathbf{p}) = (logit(p_1),...
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Un/centering an interaction term whose slope is random

I am trying to fit a GLMM using the lme4 package. As my dataset is confidential I will attempt to explain it using an analogy. I have 21 solar panels from different manufacturers (Panel_ID). Each ...
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17 views

GEE (generalized estimating equations) or GLMM (mixed effects models)

I have a repeated measurement data, The observations are single Bernoulli trials about students. Each student has 4 observations, students are grouped clustered into classes and schools. I want to ...
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Problem with finding good model fit using glmer()

I have a dataset of measurements of "Y" at different locations, and I am trying to determine how variable Y is influenced by variables A, B, and D. I also have another variable, C, that may ...
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25 views

Model residual diagnostics of gamma GLMM with log-link

I am trying to model fish length data (N > 115.000) which are highly right-skewed using linear mixed effects models. Actually all data make sense and the the extreme high values are valid ...
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38 views

MMRM(Mixed Model for Repeated Measures) in glmmTMB using R

I am currently trying to analyze data using a model called MMRM (Mixed Model for Repeated Measures).I think it was first proposed in this document. Mallinckrodt, C. H., Clark, W. S., & David, S. R....
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Can I use ROC/AUC to compare binomial GLMM models?

Is there any reason not to use ROC for evaluating the effectiveness of a binomial GLMM model with logit link? In my specific case, I have six models (one null model with two random effects, five other ...
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Is this random effects crossed design correct in my GLMM?

I am confused about how random effects are structured in my model. I've read the discussion about it Crossed vs nested random effects: how do they differ and how are they specified correctly in lme4?. ...
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How to test which of two modeling options is better: correlated model or independent models for bivariate count data?

I have modeled a bivariate count data set for a conch study, where one count is adult conch and the other is young conch, as follows: joint way to take into account the correlation between random ...
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Effect of random samples on multiple groups in double-blind study

I have four different groups of analysts, each of which was given a random sample from a pool of possible images to classify in an online double-blind study. These analyst groups were created after ...
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What does 'level' mean in regression modelling

This is a very simple question, but I'm a bit confused. I know that in GLMMs, the random effect should have a minimum of 5 'levels'. Based on this: "Random effect models have several desirable ...
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Creating interaction plots for models fit with GLMMAdaptive

I would like to create interaction plots for a model that I fit to a very large dataset by using mixed_model() from GLMMAdaptive. Interactions that I would like to plot include an interaction between ...
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34 views

How to analysis the repeated measured study where combine with matched pairs?

I am doing a study to evaluate the effect of treatment on eyes. The purpose was to explore whether the level of X protein is different between treatment group (sick eye) and normal control group (...
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How to test the effect of a grouping factor that should be random to account for repeated measures?

Experimental plan: several species of animals were observed for a year, but not regularly (some months have many observations, others have less). All individuals belonging to the same species were ...
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calculate effect size for fixed effect variable with >2 levels binomial glmm (lme4)

I have a mixed effects model with a binomial outcome which I constructed using glmer from the lme4 package in R. In the output from summary(model) I get estimates ...
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Model Verification for Gamma GLMM, different between qqplot and DHARMA

I am working with a dataset where the response variable looks like an in-between of normal and gamma distribution Edit: Including model formula and output, as requested, below  I’m using lme4 ...
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72 views

DHARMa testZeroInflation: how to interpret output?

I'm analyzing count data with a negative binomial GLMM via the R package glmmTMB and lme4. I'm running DHARMa diagnostics, one of which is testing for zero inflation and I'm having some trouble ...
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Does offset always have to be on log scale with NB GLMM?

I'm using a negative binomial GLMM with R package lme4 to detect differences in time mothers spend feeding before and after birth (inf_cat). ...
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1answer
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glmer (R) versus SAS output random effects

I have a binomial glmm model which I have analysed in both SAS and R. However, I have noticed a difference in the statistics which are given for the random effect. In SAS, there is a table called '...
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GLMM fitting - what is "variance dispersion"/"the excess variation relative to what is expected from a certain distribution"?

I'm currently fitting a poisson GLMM on my counting data with "Motherplant:Population", "Motherplant" and "Plant_ID" as random effects. While the fixed effects showed no ...
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1answer
32 views

Dealing with singularity and overdispersion in GLMM?

I'm running a GLMM through the lme4 package in R to detect differences in time spent feeding (response) before and after birth (my 2 categories in the variable inf_cat). I started with a poisson GLMM, ...
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Selecting the method to compare the frequency in two groups with repeated measures in each group

I have two dichotomous variables determining the cut-off point in the measurements taken before and after the manipulation. Not all observations are independent of each other, as for some subjects ...
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192 views

GLM to normal distribution?

I have a dataset with four variables: Body temperature (dependent variable), air temperature, ...
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1answer
32 views

The method for analyzing the repeated measures study when the data was non-normal distributions

When we conduct the repeated measures data (a continuous dependent variable) by using the method of repeated measures ANOVA, GEE or Multilevel models, the data was need follow normally distributed (...
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(G)LMM for temporally clustered, autocorrelated data

I have data from a randomised trial structured according to the image below (Rand = Randomisation, EoS = End of Study), which illustrates fictitious data from two participants. The general goal is to ...
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How to analyze the data for multiply measuring result from the mice pass the machine for Gait Analysis?

We want to compare the difference of the data from Gait Analysis between normal group and treatment group in mice. There are 6 mice in the normal group and treatment group, respectively. We plan to ...
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Choosing random and fixed effects for binomial GLMMs when the dependent variable has three levels

I'm new to statistics, so this might be a basic question. I'm trying to fit generalized linear mixed models for data where the dependent variable is categorical with three levels (True, False, Other). ...
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Inference for overall population parameters with multilevel models

I have a dataset that it is clearly need a multilevel model approach -observations from different regions-. However, I am not interesting in population parameters of regions, but overall parameters ...
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Mixed effects logistic regression type model in R - GLMER problems

I'm doing a project where I have students listen to 7 stimuli (all students listen to the same 7), and then say for each one whether that stimuli sounds more like PALM or TRAP. There are two groups of ...
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GLMM: How to impose a specific parameter (intercept or slope) for the model?

Good afternoon, I would like to know if it’s possible and how to specify parameters in a GLMM. Let’s take the example of a GLMM with random intercepts. In the following equation, the vector of fixed ...
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How to handle big count data with huge orders of magnitude in GLMMs: center & scaling but than negative values are introduced?

I'm relatively new to GLMMs and so far only handled relative data. Now I'm trying to model if the abundance of a taxon is affected in the disease state (condition) when considering random effects like ...
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how to select random effects in a GLMM?

I have data from a group of subjects (n=7) performing a two-alternative forced-choice task, where they can respond left or right. The number of trials depends on the subject in the range of 1000 to ...
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GLMM with a fixed effect 'nested' within a random effect

I am working on a GLMM regarding some organism occurrence data in relationship to climate data (over time) and habitat data (static) - my main question is how to best handle a habitat measurement that ...
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Can a linear model (LM) sample calculation be used for Linear mixed model (lmm)

I need to calculate the sample size for a study. In the studiy, we will let participants answer ranking questions about 16 pictures of 4 persons in 4 postures. Because we want to control for the ...
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What is causing the singularity in a glmm with simple random effect?

First time poster but have been very grateful over the past couple months for this forum. First and foremost, I apologize in advance if I am not following the right procedures in asking a question. I ...
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post-hoc tests for a GLMM with polynomial term

I have count data (winter bud production) from a greenhouse experiment in which 48 plant genotypes were subjected to 4 salinity treatments ranging from low to high salinity. For optimal model fitting ...
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How to explore significant interaction for two variables in a (g)linear mixed model

The (g)LMM model includes a continuous variable A (0-100) and a categorical variable B with two levels (B1, B2), if the two-way interaction between them is significant, how can I further explore this ...
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Default Priors for Intercept and Standard Deviations in R package brms

The only resource I found explaining the default priors in brms is its manual (newest version, updated 03/14/2021) for function set_prior(). For the intercept, the manual does not specify how the ...
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Calculating ICC for a beta-binomial GLMM

I understand that ICC in binomial GLMMs with a logit link can be calculated via R, where the residual deviance is (pi ^ 2) / 3. However, this is assuming that the ...
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1answer
39 views

Calculating effect size for glmm with repeated measures, what is the sample size?

I am new to effect sizes and trying to calculate it for a repeated measure GLMM that looks like this: variable ~ treatment * sampling occasion * year + (1|subject) The variable is continuous, the ...
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1answer
64 views

Generalized mixed-effect regression model (GLMM) with negative reaction times as a result of baseline RT subtraction

I am hoping to get some advice for examining differences in reaction times (repeated sampling) as a measure of cognitive load between groups. Dataset: The response variable I am using is reaction ...
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How to interpret nested GLMM results

I have a dataset like the following: ...
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21 views

How to specify random effects in logisitc mixed effects regression with multiple observations per subject but only 1 outcome per ~50 DV measurements?

I have a dataframe that looks something like this: Each subject got somewhere between 40-120 lesions in a given procedure, and I want to know which dependent variable was associated with "injury&...
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30 views

How to extract the formula of a generalised linear mixed model?

I am trying to extract the formula for a generalised linear mixed model (GLMM). I have made the model from this dataset: ...
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Testing if groups are statistically different from 0.5 in a binomial GLMM

I have a dataset where I have a binomial (bernoulli - either 1 or 0) response variable, a single fixed factor containing 3 different groups (group1,group2,group3) and a random factor specifying ...
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Books / Guides / Courses for mixed model? [duplicate]

I have started working for a pharmaceutical firm as a junior statistician recently . In the daily basis I work with lots of studies where I have to apply the mixed models in order to demonstrate the ...
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35 views

How to deal with post-stratification weights in regression settings?

I'm given a longitudinal (i.e., panel/repeated measures) dataset with 2 periods and individuals serving as clusters. The response variable is whether a person would support a healthcare bill, so it is ...
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107 views

GLM modeling binomial proportions with varying trials and probabilities

A collection of coin manufacturers, $m$, each produces a line of coins, the number of which varies by manufacturer (some produce 3 types of coins, others make 7, and so on). Each manufacturer imparts ...
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wildly different parameter estimates in Generalized Linear Mixed Model in response to conceptually irrelevant (?) change

I’m analyzing some data per GLMM with a probit link function and I'm getting some weird inconsistencies between two GLMM specifications that, in my understanding, shouldn't be all that different. Let ...

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