Has anyone an idea if it is appropriate (and if so, how?) to model a dispersion parameter in
#glmmTMB (as alternative to robust/HC standard errors) when inverse probability weights are included in the model? For which parameter(s) should the dispersion be modeled?
@bbolker.bsky.social maybe?
RE:
https://bsky.app/profile/did:plc:5kx3l44skokbyab6ycny437w/post/3lix6fep4qc2cComparing Bayesian Approaches
I have just realised that {glmmTMB} has been downloaded far too rarely so far. Maybe people haven't recognized how flexible and strong this package became? Install it now, it's the {brms} in the frequentist world!
https://cran.r-project.org/package=glmmTMB #rstats #glmmTMB
glmmTMB: Generalized Linear Mixed Models using Template Model Builder
Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
Hey
#mixedmodel #rstats peeps - anyone know of a package or function that does for
#glmmTMB what merTools::predictInterval() does for
#lme4?
#wantingToMoveEverythingOver#glmmTMB was just updated on CRAN and has some nice new features, e.g. ordered beta regression:
https://cran.r-project.org/web/packages/glmmTMB/news.html #rstats 
Daniel đšī¸
Christos Argyropoulos MD, PhD, FASN đēđ¸ 0kale/acc
Dr Mircea Zloteanu đēđđ
Daniel
jebyrnes