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 …
What is the difference between generalized estimating equations and …
The following CV questions also discuss this material: Difference between generalized linear models & generalized linear mixed models in SPSS; When to use generalized estimating equations vs. mixed …
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.
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. PQL if appropriate). …
Should I use GLMM or GAM in my analysis? - Cross Validated
Apr 13, 2022 · If you want to model individual bears as random effects then you have a mixed model, potentially a GLMM (generalized linear mixed model). A GAM (generalized additive model) is one …
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 (ChangeTotal ~ …
r - How to interpret GLMM results? - Cross Validated
Jul 24, 2020 · How to interpret GLMM results? Ask Question Asked 5 years, 4 months ago Modified 5 years, 4 months ago
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 linear mixed …
glmmTMB truncated models with zero inflation - Cross Validated
Nov 28, 2023 · I am fitting a glmm model using the R library glmmTMB for predicting a count response variable with excess-zeros and overdispersion (nbinom2> Poisson). Additionally, I am insterested in …
glmm - GEE vs Marginal Models: Are they the same? How are they ...
Mar 25, 2021 · The GEE is a marginal model. Unlike "plain" regression, such as OLS or GLMS for independent data, the GEE estimates the variance structure which accounts for correlation …