--- On Fri, 29/1/10, Dan MacNulty wrote:
The location of the knot is the key research question. My initial
approach was to use AIC to select the best-fit model from among a set of
models each with a different fixed knot. However, a reviewer has
criticized this approach, arguing that I should have estimated the knot
as a parameter because it affords a better measure of uncertainty about
the knot location.
The only thing I can think of is that you might try to go Bayesian, as
adding a weakly informative prior on such a parameter can sometimes stabablize the model.
One alternative you could do that might convince the reviewer, or at least
the editor, is to show how the likelihood changes over the values for your
knot locations, which will show that it a quite irregularly shaped
likelihood function with which most maximization algorithms will have
great difficulty (hopefully it shows multiple modes, some plateas, etc).
Good luck,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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