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Re: st: Knot optimized logistic regression

From   Maarten buis <[email protected]>
To   [email protected]
Subject   Re: st: Knot optimized logistic regression
Date   Fri, 29 Jan 2010 09:24:24 -0800 (PST)

--- 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 L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen


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