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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Improving glmm accuracy - what can I do here?
I'm working on a model in R but my validation suggests it's breaking some assumptions - non-normal residuals and heteroscendasticity. My dependent variable is highly skewed, and originally bounded (...
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Comparing GLMM with LMM with -2*log-likelihood
Is it possible/recommended to compare the -2*Log-Likelihood (-2LL) value of a Generalized Linear Mixed Model (GLMM) against the -2LL value (and/or AIC/AICC/BIC) of a Linear Mixed Model (LMM) with the ...
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Is it appropriate to use PCA scores as response variables in a GLMM to compare two experimental conditions?
I conducted a within-subject experiment with 40 participants, where each participant was exposed to two conditions. They completed a survey with nine 5-point Likert scale questions after each ...
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Mixed model estimates [duplicate]
The dataset obk.long has 3 levels for treatment, why when running a mixed model with afex is it returning estimates for only treatment 1 and treatment 2 and not treatment 3?
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Can I compare intercepts between GLMs and GLMMs to estimate the effect of a random effect? [closed]
I’m working on a statistical analysis where I’ve run both generalized linear models (GLMs) and generalized linear mixed-effects models (GLMMs) on the same dataset. Can I interpret the difference ...
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GLMM for Inference vs Prediction
I am assessing cross-sectional repeated measures data using a mixture of linear mixed models (LMM) and Generalized Linear Mixed Models (GLMM). I see in various places that GLMM is used primarily for ...
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GLMM with interaction terms between two circular predictor variables?
I am running a GLMM to see if several weather and nest box covariates influence occupancy (binary linear response). I would like to include two circular predictors (wind direction and box entrance ...
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Use of circular predictor in GLMM
I am developing a mixed-effects binomial logistic regression (using glmmTMB, family = binomial) where the response is presence-absence. One of my potential predictors is hour of day, which takes ...
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Can I use the Estimate of a model directly without considering the p-value?
This is a follow-up question of (About Multivariate Generalized Regression Mixed Models with negative binomial distribution). The research question is to get the intraindividual (within-subject) ...
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Modeling Transitive Preference
I've conducted a preference test twice on 10 subjects, presenting them with three options in all six pairwise combinations (AB, BA, CB, BC, AC, CA).
I need to determine the following: if each subject ...
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Mixed effects models with only categorical data?
This is my first time trying to run any type of mixed effects models. I have a dataset where I was instructed to use some form of mixed effect modeling (lme4 package) to see if functional traits of my ...
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simr package : powerCurve does not give the same results as powerSim
I plan to run a pharmacokinetic study, namely testing same individual before/after treatment (repeated measures). These individuals are distributed in different treatment groups, with expected ...
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Strange output for glmmTMB and pairwise comparison
I am running a glmmTMB to see if there is a significant difference in survival to the eyed egg stage (proportional data between 0 and 1) depending on what genetic male type was used (W, YY, or F1) to ...
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Characterize interaction effect from binomial glm
I have made a binomial glm which describes how a complexity score (integer value 0-5) and an experimental treatment (factors A,B,C) affect a ratio of successes to failures (x, y) (both x and y are ...
Elliot Howard-Spink
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Mixed Effects models approach?
I've been debating on a more deliberate diving into working with mixed models but I am slowly feeling overwhelmed. I've been going through resources (tutorials, webpages, books, etc) and have feeling ...
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GLMM Model Averaging with Predictor Multicollinearity
I am running GLMM models to determine how environmental factors influence bird collisions. I've obtained a list of candidate models with delta AIC less than 2, and I want to perform model averaging.
I ...
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Intercept estimates VERY different comparing glm and glmm
Can anyone explain the following puzzling phenomenon? I'm fitting a binomial glmm using glmer from the lme4 package of R. The mean of the binary response variable in the dataset is about 0.1. When I ...
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Multilevel Modeling in Linear Mixed Models versus Generalized Linear Mixed Models
I am analyzing a data set that includes several discrete and continuous outcome variables (DV). For the continuous DVs I intend to use Linear Mixed Models (LMM) processed in SPSS. For the discrete ...
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Reporting significance of fixed effects in clmms - when to use ANODE tables?
I am working on some mixed effects models for ordinal outcomes using clmm. I have settled on my final model, and now want to present the findings. On reading around, I see the use of ANODE tables both ...
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Linear mixed model, negative information criteria values and Hessian matrix not positive definite?
I'm trying to perform this operation in R.
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Tradeoff between autocorrelation and memory in a GLMM
I am working with a large dataframe in R. It is a BACI design (Before-After-Control-Impact). I am interested in seeing if the interaction between Treatment (0 = control, 1 = impact) and Period (Before,...
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Fitting random slope for a subject-level predictor
In a nutshell, I am trying to understand whether it makes sense to include random slopes for group-level (or subject-level) predictors in a mixed effects model?
Some Background: I am fitting a mixed ...
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Looking for a modification of variable importance in ANCOVA-type glmm
This question is about a statistical concept I think should exist. I would like to know if it has a name and hopefully an R package that will implement it. It is related to variable importance/...
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General Linear Mixed Model: How do I fix 'Rescale variables? Model is nearly unidentifiable' error on glmer
I'm trying to fit a generalized linear mixed model (GLMM), but I'm getting a persistent error. I'm looking at the relationship between weather (continuous variables: rainfall, maxtemp, and mintemp) ...
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How reasonable is it to divide an offset by an integer to make the model non-singular?
I have been trying to fit a GLMM (Poisson) into a dataset which has flock size as response variable, climatic data as fixed effects, and different Zoos in the USA as random effects. I am a novice in ...
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GLM Multiple Comparisons
I am performing several Generalized Linear Models in my analysis and I am wondering which method to use for adjusting p-values due to multiple comparisons.
I have 4 outcomes (judgement of intensity ...
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Choose sample size in Linear mixed models. Ethical considerations
There are no reference articles on this topic, the linear mixed model requires real data on results to calculate the sample size, unlike an anova model that requires data on power, significance and ...
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Is there an way to model random effects in a design that is typically analyzed by the McNemar test?
My question is: if in a study with paired binary response data (where McNemar test is often used) we can use the exact binomial test to test the odds ratio, is it possible to model the same odds ratio ...
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R throws deficiency warning when running a logistic regression (LMM)
I have never run a logistic regression analysis (linear mixed-effects model) in R, but it seems to be a reasonable approach to answer the question as to what extent condition BB affects the ...
Andreas
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Using glmmPQL with known correlation matrix (GBLUP model)
I am working on a project attempting to apply a GBLUP (Genomic Best Linear Unbiased Prediction) model to genetic disease data. My goal is to model the probability of an individual developing a disease ...
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Confidence interval for GLMM
I am conducting a GLMM for my bachelors thesis and I am wondering, how I can calculate and whether it is common to report confidence intervals for the models' estimates.
This is the model I fitted on ...
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Including random effect reduces model fit
I am fitting a zero-inflated negative binomial GLMM to model counts. Fixed effects are all categorical except Effort_sq which are non-zero values. The experiment is performed several times within a ...
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Is it appropriate to calculate odds ratios from random effects glmm output?
Is it appropriate to calculate odds ratios from random effects glmm output?
about the data:
grown (binary): whether flower grows over a certain height (TRUE/FALSE)...
dasyer5
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GLMMs with crossed random effects: How do I quantify the reduction in random effects variance of including fixed effects? Or, indeed, should I?
I am modelling test score outcomes (0/1) using a GLMM with crossed random effects for persons and items. As I add significant fixed effects estimates for person and item, the variance estimate for the ...
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Binomial mixed model with conditions only ever 'succeeding'
I've been wrestling with getting some models to converge and make sense and think I've identified the problem, but am now looking for a solution (and if you agree with the "problem").
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(When) Does GLMM provide better predictions than logistic regression?
I am trying to test statsmodels GLMM vs logistic regression (by either statsmodels or scikit-learn - see the code with a toy example below). I understand the ...
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How can I fit a model with a random intercept and slope using INLA?
I'm attempting to replicate the form of a negative-binomial GLMM that I used to run via glmmTMB::glmmTMB() using INLA::inla(). ...
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How to fit a GLMM with multiple levels of nesting
I have some data I am struggling to process at the moment. I have landed on using generalized linear mixed models (GLMMs), but I am having a very hard time wrapping my head around it.
I have a large ...
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Most suitable statistical model in an unbalanced, repeated-measures, paired observations setting
I've got the following dataset. For every subject, brain data has been recorded across different days, and for each day, in different states (sleep/awake). Data has been recorded in many channels ...
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Why does higher variance between clusters increase the power to detect the effect in Poisson mixed GLM?
I simulated the dataset below and I am trying to fit the Poisson GLMM with random intercepts and calculate the power to detect the effect of $x$.
When I increase the variance between the clusters ($0....
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GLMM logistic regression with interactions
I have been working on a mixed effects logistic regression model to analyze some data, and I'm seeking some clarification on interpreting the results, particularly when incorporating interaction terms....
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Sample size calculation for generalized linear mixed models - variance assumption for the random effect
Introduction
I would like to perform a sample size calculation for the Poisson generalized linear mixed model.
I will leave out irrelevant details, I need to deal with clustered data and the model has ...
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How to deal with under-dispersion in negative binomial GLMM?
I have some animal species. I am interested in seeing what is the relationship between the area they occupy (my response variable, p, which is a count of cells) and ...
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Non-transformed Log scale response variable in LMM - which distribution to use?
I am currently modelling tea bag index results across different forest "treatments" to infer differences, effect sizes and influence of covariates. One element of these results and a ...
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Mixed models - interactions or individual regression
I am using LMMs and GLMMs(where necessary) to model carbon pools between different treatments. i.e specifically intrested in contrasts.
These pools are divided between different groups e.g. diferent ...
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Model selection for glmer in R
I am trying to make a model for the different amount of species caught in different traps in 3 different locations on 3 height levels, along with 3 transects per location (resulting in 9 traps per ...
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GLMM with negative binomial- narrowing down variables & choosing a model
I'll start by saying apologies for perhaps not wording things correctly, as stats is not my first language (lol). Please let me know if there is any other info I need to provide to make this easier to ...
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Handling Nested One-Level Random Effects in Linear Mixed Models in R
I am constructing a statistical model to examine the relationship between thrust force and kinematic data collected from tags attached to animals. The data is structured with 'slip' as a random effect ...
Joji
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Model failed to converge (gamma model, self-paced reading data)
I'm trying to run a Gamma analysis in a self-paced reading data. However, the model successively fails to converge. I've seen some answers here trying to solve this problem for other people, but none ...
Wellington Almeida