Hi Ben / List

Thanks for the reply, and the more compact code. I should probably have provided more context to the post in the first instance. The simulated data do indeed lend themselves well to being analysed with an observation level random effect (OLRE), but that’s because the data are explicitly designed to investigate the pitfalls associated with not explicitly modelling overdispersion when it is present. 

I plan to do this for data generated as in the original email (overdispersion added to the linear predictor by OLRE), and also zero-inflated data. My first thought was that it would be good to have an initial section dedicated to how you measure the presence of overdispersion in a mixed model context, and the parametric bootstrapping approach seemed like a nice way to dispense with the need to estimate residual df in a mixed model. I just wanted to make sure it seemed sound before putting it in the kind of place where it might invoke the ire of a reviewer. 

Regards

Xav






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Dr Xavier Harrison
Institute Research Fellow
Institute of Zoology
Zoological Society of London
Regent's Park
London NW1 4RY
xav.harrison@gmail.com
+44 (0) 207 449 6621
www.zsl.org/xavierharrison/













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