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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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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Manual variable selection in GLMM
I'm modeling my data using GLMM with 1 random factor and 10 variables that are of interest. Instead of using automatic selection, I started with the full model (including all variables except for the ...
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Confused by GLMM strange pseudo r square output
Someone from another lab is trying to run a GLMM model and estimate the pseudo R square of the model. So far this is the output from the anova and ...
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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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Are the GLMM's appropriate for me and what resources can help me understand,
The participants had to perform 3 blocks and 6 conditions and I measured success or failure. I would like to know if there is a significant difference between the blocks, between the conditions and ...
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Which test for a withinparticipant design with 2 categorical variables (with each participant having a value in each condition)
Design : two categorical variables. First : the independent variable : "type" with two conditions : intra & inter. Next, the measured variable : "consistance" with two ...
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Are overdispersion and underdispersion in a binomial logistic regression model an issue if the model is not being used to make predictions?
If a binomial logistic regression model is being used strictly to identify variables that have an impact on the dependent variable but is not being used to make predictions, are underdispersion and ...
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Fixed or random effect for time in GLMM
I'm using GLMMTMB to build a model that predicts the state of fish stocks based on management attributes. The model contains an AR1 term for each stock and regional and taxon level random effects to ...
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What post hoc to use after finding significant main effects and simple interactions in a GLMM?
I have a experiment with multiple nominal and ordinal variables of interest ($7\times4\times3\times2$) as well as 3 nominal nuisance variables ($2\times2\times2$). The one outcome variable is binary: ...
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emmeans properly conducts multiple comparison for one glmmTMB model but not the other
I have two datasets from different years. They are structured almost identically. One is substantially larger than the other and has more time points. When I prepare a negative binomial generalized ...
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glmmTMB results in R summary() or Anova()?
I am wondering how to analyze differences between subspecies. I want to see if body mass differs between 3 subspecies of rodent and if sex and reproductive status are also different. We then want to ...
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How to write the difference formula for Linear Mixed Effects Models (with lmertest or lme4)?
I have a training dataset with:
...
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Examining Interaction Terms in Mixed-effect Modelling
I am very new to LMM and will be appreciated it if I could have your suggestions.
I running a study to gauge whether there is an interaction effect among the number of new words in a text (text ...
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Zero inflation with no zeros in data?
I am investigating feeding rates in great apes. Because I am using count data, I built a generalized linear model with a Poisson link function. So I put the number of items in a bundle as a response ...
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Making a valid inference from higher level fixed predictors in mixed model
I'm planning a field study in which pollinators will be caught from traps in the canopies of 12 woodlands. Within each woodland ~4 traps will be placed. Traps from different woodlands I consider to be ...
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Valid to only use random slope for linear term when the variance of quadratic slope term is near-zero?
I am performing some habitat analyses across a large area and am incorporating random slopes in my models for landscape predictors and a random intercept for individual animal. According to this post ...
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Mixed Model logistic regression with lots of zero's
Imagine a cluster randomized trial with a binary outcome. Now let's say that the clusters aren't too large (e.g. 10 observations per cluster) and that in the control arm, the event is not so abundant (...
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Should I be using Linear Mixed Models, or something else?
I am conducting repeated measures research on sleep quality (outcome variable) assessed daily over 2 weeks (14 time points). My research question is about determining which behaviours engaged in on ...
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Fitting a linear mixed model on repeated measurements data, do I in- or exclude patients with only 1 observation?
I have a dataset of about 300 patients of which 100 have repeated observations of the outcome (2-6 observations per patient) and 200 have only 1 observation of the outcome.
To determine what the risk ...
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When does a group specific dispersion parameter for the negative binomial distribution make sense?
If you have overdispersed observed abundance of multiple species including zero inflation the negative binomial distribution seems to be a reasonable choice. But if some species occur much more ...
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R packages for psuedo R squared disagreements
I'd like to report a psuedo-R^2_glmm for some glmms I've made. Oddly, I've found each R package I've tried gives a different result, while I thought these all are doing the same thing in principle. At ...
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Random effects, single observtion mesaured multiple ways
I am constructing some binomial glmms and thinking about my random effects.
Let's say I measured the number of bugs on 3 different plant types, and the abundance (relative area) of those plant types. ...
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Transposing an R equation to its algebraic form: a linear mixed model with random intercepts but no random slopes and an interaction term
I'm working on a psychological experiment using Linear Mixed Models (LMM). In this model, I have a random intercept for each subject, but I do not have random slopes.
With this model, I want to check ...
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Confidence interval of the sum of beta coefficient
I'm currently trying to estiamates the evolution of runner speed in function of distance and sexe. I'm building a GLMM Gamma Model. For thoses using R, here is my model.
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How to generate simulation data based on a two-way ANOVA in the previous research?
I'm trying to generate simulation data based on the results of a two-way ANOVA in a previous study, and to fit a generalised linear mixed effect model (GLMM) to the simulation data and calculate the ...
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Can I consider interaction effect between two principal components?
I ran a PCA on five variable and got PC1, PC2 as the main axes. Then I want to run a GLMM with binomial distribution to see how these two PCs influence the response variable. My question is if I can ...
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Help interpreting gamma (log) GLMM results in R
I am not a statistician and am having trouble interpreting my results below... would really appreciate some help!
My dependent variable is Euclidean Error and my independent variables are Light, ...
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Inclusion of values that can only be zero in Poisson glmer
I have carried out a biological experiment in which the dependent variable is female propensity to mating, measured as the number of times a female animal accepts a mating attempt from a male.
I have ...
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Do Marginal Models by nature not have enough degrees of freedom (and therefore cannot fit)?
In the following text from Agresti's Foundations of Linear and Generalized Linear Models, I just don't get how equation 9.2 makes any sense. We are making a separate linear relationship between each ...
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Best way to visualize the results from a glmm with count data
I am trying to analyze a dataset of counts of plants from multiple different sites. Each site has a treatment group and a control group, and each site was counted once before treatment and once after ...
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Empirical Bayes prediction
I've been working with a GLMM in SAS. Using the proc GLIMMIX procedure, I've extracted the EB estimates of the random-effects.
I was looking into empirical Bayes estimates and their predictive power.
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What is the best way to compare fixed and random effects of a GLMM?
I am doing a research in which i am trying to measure the importance of the doctor that is in charge of a patient in a medical decision. For that (and others reasons) i have used a GLMM using lmer4 ...
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GLM with scores/principal dimensions from MCA
I hope someone can help me understand how to run this analysis!
I have a dataset with many categorical variables (i.e. color, pattern, texture) associated to each animal in each interaction between ...
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Interpreting p-value from GLMMTMB model
I'm analyzing count data from an experiment, where I want to study whether colonies of ants with different ratios (0, 50 100) of infected workers have different foraging activities. I am using the ...
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Output from glmer with a probit link (lme4 package in R)
I want to estimate the fixed effects and the covariance matrix (or standard deviation of the random effects terms) for a GLMM with a probit link using glmer. Most of the documentation that I can find ...
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Is a tilde or an equals sign correct in linear mixed model formulas?
I know the formula for a linear mixed model (LMM) is often (always?) written with a tilde, rather than an equals sign, between the LHS and RHS. For example, one would write
outcome ~ 1 + var1 + (1|...
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Convergence and rescale error when running inverse gaussian GLMM
I am trying to analyse response times from a study on hormonal contraception and it's effect on RT in anagram and logic tasks with a mixed effects GLMM
Response time is in seconds and varies from ...
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residuals for model validation cheatsheet
I'm not statistician and I do not do statistical analysis every day. Thus when I do need to run my analysis I frequently find myself looking at text books and browse the web to refresh my memory.
In ...
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lmertree: Partitioning factor with too many levels?
I am new to lmertrees. I am having trouble analyzing how individual stimuli in my data clusters together on the basis of how some participants answered to them in three different conditions. My code ...
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I am getting (slightly) different results each time I run the glmmadmb function from glmmADMB, and I don't understand why
Background: We are investigating the effects of two environmental variables, temperature and evapotranspiration, on annual infection rates in mosquitoes. We want to identify the months with conditions ...
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Is there quasi-seperation here (glmm, logistic regression), and how to take care of it?
I am running a mixed model (logistic regression) using the glmer function of lme4. I have a binary response variable "Germination", one categorical variable "Habitat" with 4 levels ...
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R squared for a zero-truncated negative binomial model
Does anyone know how to calculate R squared for a zero-truncated NBM (ZTNB)? I used the methods developed by Nakagawa and Schielzeth 2013 and Nakagawa et al. 2017 to calculate R squared for Poisson ...
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Random effects model for longitudinal data with repeated measures at each time point
Scenario 1: I have data for 100 patients at 5 time points each. Generally, this is a classic case where I can fit the following random effects linear model:
$$Y = \beta_0 + \beta_1*t_{ij} + b_{0i} + ...
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