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Re: st: Suest and Cox regression


From   Steve Samuels <sjsamuels@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Suest and Cox regression
Date   Wed, 28 Jul 2010 12:56:47 -0400

Richard, it is not true of  -streg-, because that command is based on
standard likelihood theory. To give a familiar example, in multiple
linear regression, if the error term is assumed to have a Gaussian
distribution, the  likelihood score for an observation is its
residual: a function of  its y,  x's and the estimated betas.  The
equations for forming the covariance matrices in -suest- (see the
manual) don't work for -stcox- because of the non-standard scores.

Steve


On Wed, Jul 28, 2010 at 12:23 PM, Richard T. Campbell <dcamp@uic.edu> wrote:
> Thanks Steve, you are, of course, course correct.
> But is this not true also for -streg-? And -suest- works nicely
> after streg. I guess I don't understand why -stcox- should be
> any different but there is obviously something I am missing here.
>
> At 11:00 AM 7/28/2010, Steve Samuals wrote:
>>
>> I'm not expert in the theory of -suest-, but after looking at the
>> equations in the manual entry, here's my guess: -suest- works when the
>> program computes a score for each observation that is a function of
>> the regression coefficients and of the observation's data.  In Cox
>> regression, the score is _also_ a function of a random parameter  that
>> depends on who is in the observation's final risk set.
>>
>> Steve
>>
>
>
>
>
>
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-- 
Steven Samuels
sjsamuels@gmail.com
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