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Re: st: linear probability model


From   SR Millis <aa3379@wayne.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: linear probability model
Date   Wed, 23 Jun 2010 09:53:16 -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

--- On Wed, 6/23/10, dk <statad27@googlemail.com> wrote:

> From: dk <statad27@googlemail.com>
> Subject: st: linear probability model
> To: statalist@hsphsun2.harvard.edu
> Date: Wednesday, June 23, 2010, 10:01 AM
> 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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