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 …
When to choose GAM over GLMM and how to include random effect …
After removing the outliers, the overdispersion is solved. So now I have three models that seem to be good to go. The first model is GLMM with negative binomial distribution. The 2nd model is the Zero …
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 …
What is the difference between ANOVA, Linear Regression, GLM, and …
Dec 3, 2016 · One of the difficult aspects of statistics that I have found is the nomenclature and terminology being used. I would like to know what the difference between the following 'techniques' …
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 …
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 to see how …
mixed model - How to select the family for a GLMM with non-normal ...
Jul 15, 2020 · How to select the family for a GLMM with non-normal, continuous data and lots of zeros Ask Question Asked 5 years, 6 months ago Modified 5 years, 6 months ago
r - How to interpret GLMM results? - Cross Validated
Jul 24, 2020 · How to interpret GLMM results? Ask Question Asked 5 years, 6 months ago Modified 5 years, 6 months ago
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). …
How should I interpret the dispersion parameter in my glmmTMB …
Aug 4, 2025 · I have run a lognormal GLMM using the glmmTMB package, and I could use some help understanding the dispersion parameter. It is very large (2210), but there are no model convergence …