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Re: st: Understanding Factor variables - is order significant ?


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Understanding Factor variables - is order significant ?
Date   Wed, 26 May 2010 00:22:22 -0400

This is a perplexing state of affairs! I don't know how to explain this!

I hope someone can help explain!

Michael, I am relieved that someone else is confused! Tweaking your code a bit,

use http://www.ats.ucla.edu/stat/stata/dae/poissonreg, clear
gen himath = math > 50
poisson daysabs himath#male, nolog
poisson daysabs ib0.male#ib1.himath, nolog
poisson daysabs ib1.himath#ib0.male, nolog
poisson daysabs ib0.male##ib1.himath, nolog
poisson daysabs ib1.himath##ib0.male, nolog

The first 2 models give the correct result -- LR Chi-square = 202.49. The 3rd gives the incorrect result of LR chi-square = 144.99. The last 2 commands, using ## instead of #, also give the correct results.

In the few examples we've tried where we knew the correct answer, it looks like interactions of the form b0.x1#b1.x2 worked fine but b1.x2#b0.x1 caused problems. Further, plain old regress seems to work fine regardless of how you do the interactions but ml techniques like poisson and ologit have problems.

I strongly suspect there is some sort of bug here. But if not, maybe we'll get a fascinating explanation that will greatly add to our understanding of interaction effects!

-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam

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