RE: st: margins vs. lincom

["Visintainer, Paul" <Paul.Visintainer@baystatehealth.org>]

Thanks, Michael.  That was my hunch since the discrepancy grew smaller as the sample size increased.

-p

________________________________________________
Paul F. Visintainer, PhD
Baystate Medical Center
Springfield, MA 01199


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Michael N. Mitchell
Sent: Thursday, December 16, 2010 1:54 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: margins vs. lincom

Dear Paul

   The difference appears to be that -lincom- is using a t-distribution and -margins- is 
using a z distribution. See the output below my signature based on your example. In 
looking at the "Methods and Formulas" section of the -margins- documentation, it refers to 
the use of maximum likelihood estimation. My hunch is that is the reason that the z 
distribution is used, but someone might have something better than a hunch.

I hope that helps,

Michael N. Mitchell
Data Management Using Stata      - http://www.stata.com/bookstore/dmus.html
A Visual Guide to Stata Graphics - http://www.stata.com/bookstore/vgsg.html
Stata tidbit of the week         - http://www.MichaelNormanMitchell.com

-----------------------
Output
-----------------------

. clear

. webuse margex
. set seed 1
. sample 1     // draw a 1% sample of the data
. regress y i.sex
(output omitted)
. margins sex

Adjusted predictions                              Number of obs   =         30
Model VCE    : OLS

Expression   : Linear prediction, predict()

------------------------------------------------------------------------------
              |            Delta-method
              |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          sex |
           0  |   62.77647   4.230417    14.84   0.000     54.48501    71.06794
           1  |   72.60769   4.837667    15.01   0.000     63.12604    82.08935
------------------------------------------------------------------------------

. lincom 1.sex+_cons
  ( 1)  1.sex + _cons = 0

------------------------------------------------------------------------------
            y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          (1) |   72.60769   4.837667    15.01   0.000     62.69818     82.5172
------------------------------------------------------------------------------








On 2010-12-15 1.38 PM, Visintainer, Paul wrote:
> clear
> webuse margex
> sample 1     // draw a 1% sample of the data
> regress y i.sex
> margins sex
> lincom 1.sex+_cons
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