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Re: st: RE: FITINT: does it test all two-way interactions simultaneously?


From   John LeBlanc <leblancj@dal.ca>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: FITINT: does it test all two-way interactions simultaneously?
Date   Wed, 20 May 2009 08:21:26 -0300

You're right; fairly easy to test. Here are the results:
I tried a smaller model with three dependent variables, call them A B & C. fitint put in all 3 interaction terms (i.A*i.B, i.A*i.C, i.B*i.C) along with main effects. It then removed each interaction term one at a time and calculated the lrtest comparing the model with 3 interaction terms and the nested model with 2.

My question is now whether or not this is a reasonable way to look for potential two-way interactions, ie., testing each in the face of all other possibilities? Using a dataset of 1495 obs, I created a model with 8 dichotomous predictors. Therefore main effects plus two-way interactions creates a model with 8 main effects & 28 interactions. Is it reasonable to test each interaction in the presence of all possible other interactions or should each interaction be tested only with the main effects?


If it is, here is my proposed approach:
1) use fitint to look for potential candidates for a model, e.g., select interaction terms whose p-values are lower than some probability, say <0.1 or 0.2.
2) Create new model with main effects plus the interactions from step 1)
3) Test each interaction term's contribution to the model using lrtest on the model with and without that term.
4) Keep those interaction terms where lrtest p-value < 0.05.

Does that seem like a reasonable way to look for interaction terms? I've also thought about a purely hypothesis-driven approach to creating and testing interaction terms but I must say, this 'fishing expedition' approach did uncover some sensible interactions that I would not have thought of looking for.

John

sjsamuels@gmail.com wrote:
John, this seems to be a question that you can answer by test which
specifies a few interaction terms. Be sure to report back your
findings.

-Steve

On Tue, May 19, 2009 at 12:20 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
-fitint- is a user-written program from SSC. Please remember to specify
where user-written stuff you refer to comes from.

In this case, I don't recognise either of the authors as contributors to
the list. Either way, if you get no good answers to this question, you
may need to look at the code -- which appears to be well structured and
commented -- and/or to contact the program authors directly.

Nick
n.j.cox@durham.ac.uk

John LeBlanc

I have an -ologit- model with 8 predictor variables and fortunately a
large dataset. I'm using -fitint- to see if there are any interesting
two-way interactions among the 28 possibilities. Does -fitint- put all
28
in simultaneously or does it (I hope) test them one by one?

by the way, what is the purpose of the -factors- option? At this point,
I'm simply copying all dependent variables into both -factors()- &
-twoway()-. I can't figure this out from the .hlp file.

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Regards, John LeBlanc

_________________________________________________________



John C. LeBlanc, MD, MSc, FRCPC
Associate Professor

Pediatrics, Psychiatry, Community Health and Epidemiology

Dalhousie University



IWK Health Centre              Work phone: (902) 470-8930

5850 University Avenue         Work fax:   (902) 470-6913

Halifax, Nova Scotia           Email: John.LeBlanc@Dal.Ca

B3K 6R8 CANADA                 Pager: (902) 470-8888

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