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st: btscs, cubic splines and predicting meaningful values


From   "Lukas Kasten" <lukas.kasten@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: btscs, cubic splines and predicting meaningful values
Date   Thu, 21 Jan 2010 16:58:41 +0100

Dear all,

i am a student of international relations and I have one short question for you:
I am working  with a tscs- structured dataset and I am computing a logit 
modell with  natural cubic splines following Beck, Katz and Tucker (1998) to 
control for time dependency. I used the - btscs- package to generate the 
necessary variables spellcount and _spline*
The command is as usual:

logit depvar idepvar1 idepvar2 ... spellcount _spline1 _spline2 _spline3, vce(robust)
I now want to compute perdicted probabilities with  - prvalue - .

My main question is, how to set the values of the variables spellcount and spline1 - spline3? Does it really make sense to set them on their mean? Or e.g. should I take the mean duration time until the analysed event occurs and set the splines accordingly to that value? (For example if the mean duration time is 5, then using - prvalue- I could set the spellcount on 5 and set the splines on the values which were computed by - btscs - for a duration time of 5.)
Is there any good procedure for setting the splines on meaningful values so 
that you can interpret the perdicted probabilities in a meaningful way?
I already had a look on some publicated articles in which also splines and 
btscs- procedure were used. Most of them set the splines on their means, but 
I am really not sure if that is correct.
I would be very thankful for any tips or hints..
best regards
Lukas
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