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Re: st: RE: linear probability model


From   SR Millis <srmillis@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: linear probability model
Date   Wed, 23 Jun 2010 09:52:24 -0700 (PDT)

The fundamental issue is the type of response variable that you have.  If it is binary, you would want to use a logit or probit model---not a linear model.  If your response variable is continuous, you would use a linear model.

Scott Millis


> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu]
> On Behalf Of dk
> Sent: Mittwoch, 23. Juni 2010 16:02
> To: statalist@hsphsun2.harvard.edu
> Subject: st: linear probability model
> 
> What are the advantages of linear probability model over
> probit and
> logit. i have read some where that linear probability model
> fits best
> for very large sample, where maximum likelihood with probit
> and logit
> does not work can any one explain this.
> 
> 
> Thanks in advance,
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