Greetings --

A new goodness of fit method has been implemented in MARK -- referred to as the 'Fletcher c-hat', given the conceptual origins in an interesting paper by David Fletcher:

Fletcher, D. (2012) Estimating overdispersion when fitting a generalized linear model to sparse data. Biometrika, 99, 230-237.

Gary has implemented the Fletcher c-hat in MARK, and it seems to work very well (based on simulation experiements conducted to date), for certain types of models. Beyond its 'robustness' , the Fletcher c-hat takes only milliseconds for MARK to calculate (in fact, MARK generates the Fletcher c-hat for all models as they are optimized), which is arguably an advantage over (say) the median c-hat.

The details are in the newly revised Chapter 5, section 5.8.