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  1. Diagnostics for generalized linear (mixed) models (specifically ...

    Fit the full GLMM. Insufficient computer memory o r too slow: reduce model complexity. If estimation succeeds on a subset of the data, try a more efficient estimation algorithm (e.g. …

  2. Difference between generalized linear models ... - Cross Validated

    The following CV questions also discuss the relationship between GEE & GLiMMs: What is the difference between generalized estimating equations and GLMM; When to use generalized …

  3. Non-normality in linear mixed models/GLMM - Cross Validated

    A GLMM was considered but given that the outcome variable is dive depth there is no obvious distribution candidate for a GLMM. On thing to consider is whether the outcome is bounded.

  4. r - How to interpret GLMM results? - Cross Validated

    Jul 24, 2020 · How to interpret GLMM results? Ask Question Asked 5 years, 3 months ago Modified 5 years, 2 months ago

  5. r - Should I use a linear mixed model or a ... - Cross Validated

    Jun 18, 2019 · I have a test dataset with repeated measures, different individuals sampled at different time points, here measured in days. I want to know if I should use a GLMM or a LMM …

  6. What is the difference between generalized estimating equations …

    How does this differ (in terms of the conclusions I can draw and the meaning of the coefficients) from a GLM with mixed effects (GLMM) and logit link? More detail: The observations are …

  7. Interpreting a generalised linear mixed model with binomial data

    Jan 14, 2020 · The interpretation is the same as for a generalised linear model, except that the estimates of the fixed effects are conditional on the random effects. Since this is a generalized …

  8. Generalized linear mixed models: model selection

    mixed-model model-selection aic glmm stepwise-regression Share Cite Improve this question

  9. glmm - Interaction using generalized linear mixed model - Cross …

    Sep 8, 2020 · I am conducting a GLMM. I currently have two independent variables (𝑥1, 𝑥2) and a dependent variable (𝑦) - all factors (either 0 or 1). m <- glmer (y ~ x1+x2+x1:x2 + (1 | …

  10. Understanding Interaction Term In GLMM - Cross Validated

    Mar 17, 2023 · Hoping to get some clarification on my understanding of interaction terms in a GLM model I have produced. I have written the following model interactionmodel <- lme …