Open mebrooks opened 4 years ago
The best citation I've found so far is: Miller, Timothy J. (2013) A comparison of hierarchical models for relative catch efficiency based on paired-gear data for US Northwest Atlantic fish stocks. Canadian Journal of Fisheries and Aquatic Sciences. 70(9): 1306-1316. https://doi.org/10.1139/cjfas-2013-0136
See also Harrison XA. 2015. A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution. PeerJ 3:e1114 https://doi.org/10.7717/peerj.1114
Eventually it would be nice to add the beta-binomial distribution to handle overdispersion. For now, the only way to handle it is with an observation level random effect.
Use the robust method
dbetabinom_robust
recently written for glmmTMB by kaskr.See section 4.1 of Tom Mitchell Elliott's master thesis for an attempted implementation of this in a Bayesian context (it had convergence difficulties). Or see Kitakado et al (2002) for a publication suggesting that we might need this.