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st: RE: non-linearities in ml


From   Timothy Mak <[email protected]>
To   "[email protected]" <[email protected]>
Subject   st: RE: non-linearities in ml
Date   Wed, 31 Jul 2013 16:50:02 +0800

<>

I think if you transform your variables as in: 
z1 = b1b2
z2 = b1b3log(b3)
z3 = b1b3

your argument inside invlogit() becomes a linear function of z. 
b3 then becomes exp(z2/z3)
and from that you can work out b1 and b2. 

Tim

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Ishani Tewari
Sent: 31 July 2013 10:22
To: statalist
Subject: st: non-linearities in ml

Dear all,
I need to estimate a logit where the parameters (beta1,beta2,beta3)
enter very non-linearly:.

lnf=ln(invlogit((X1^beta1')*(`beta2*X2+`beta3'*log(`beta3'/X1)))) if y1==1
lnf=ln(invlogit(-(X1^beta1')*(`beta2*X2+`beta3'*log(`beta3'/X1)))) if y1==0

Can I (should I) still use the "lf" model?

thnks
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