Dear R-help, I was recently wanting to use GEE with the negative binomial "family". It seems that this is lacking in the otherwise excellent implementations of the GEE methodology ( packages: gee, yags, geepack). I would have thought it a simple step to allow the creation of a family, i.e providing the link function (log mu) and the variance function (mu + mu^2/theta) , assuming theta is specified; and then to let the gee code do the business in a similar fashion to glm. However the gee codes all seem to rely a set of C routines with either the normal, poisson, or binomial, hardwired in. Does anyone have any suggestions for a way round this problem for the future (I had to resort to using Stata), or maybe more realistically, how much work it would take to build an extendible version of the gee "algorithm"? thanks Simon Bond.
On Tue, 27 Sep 2005, Simon.Bond wrote:> > Does anyone have any suggestions for a way round this problem for the > future (I had to resort to using Stata), or maybe more realistically, how > much work it would take to build an extendible version of the gee > "algorithm"? >I don't think it would take that much work [and I've done it a couple of times, once in XLISP-Stat and once in SPIDA]. An entirely interpreted implementation will be relatively slow, though it might be possible to improve that quite a bit with sparse matrix techniques. -thomas
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