Good idea, I made these changes in my GEE branch (also mentioned marginal
estimates and tests which were previously not mentioned).


On Sat, Feb 22, 2014 at 4:01 AM, Josef Perktold <notifications@github.com>wrote:

> In docs/source/release/version0.6.rst:
>
> > +ind = Independence()
> > +md1 = GEE.from_formula("y ~ age + trt + base", data, groups=data["subject"],\
> > +                       covstruct=ind, family=fam)
> > +mdf1 = md1.fit()
> > +print mdf1.summary()
> > +
> > +
> > +The dependence structure in a GEE is treated as a nuisance parameter
> > +and is modeled in terms of a "working dependence structure".  The
> > +statsmodels GEE implementation currently includes five working
> > +dependence structures (independent, exchangeable, autoregressive,
> > +nested, and a global odds ratio for working with categorical data).
> > +Since the GEE estimates are not maximum likelihood estimates,
> > +alternative approaches to some common inference procedures have been
> > +developed.  The statsmodels GEE implementation currently provides
> > +standard errors and allows score tests for arbitrary parameter
>
> minor add robust: "provides robust standard errors"
>
> aside: we also have wald tests
>
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> .
>