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The '''`regress`''' command fits a [[Statistics/OrdinaryLeastSquares|linear model]]. '''`-regress-`''' fits a [[Statistics/OrdinaryLeastSquares|linear model]].
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[[https://www.stata.com/manuals/rregress.pdf|Stata manual for regress]] [[https://www.stata.com/manuals/rregress.pdf|Stata manual for -regress-]]

Stata regress

-regress- fits a linear model.


Usage

. webuse auto
(1978 automobile data)

. regress mpg weight displacement

      Source |       SS           df       MS      Number of obs   =        74
-------------+----------------------------------   F(2, 71)        =     66.79
       Model |  1595.40969         2  797.704846   Prob > F        =    0.0000
    Residual |  848.049768        71  11.9443629   R-squared       =    0.6529
-------------+----------------------------------   Adj R-squared   =    0.6432
       Total |  2443.45946        73  33.4720474   Root MSE        =    3.4561

------------------------------------------------------------------------------
         mpg | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      weight |  -.0065671   .0011662    -5.63   0.000    -.0088925   -.0042417
displacement |   .0052808   .0098696     0.54   0.594    -.0143986    .0249602
       _cons |   40.08452    2.02011    19.84   0.000     36.05654    44.11251
------------------------------------------------------------------------------

Factor Variables

To regress on the levels of a variable rather than its numeric value, prefix the variable name with i..

To regress on an interaction of variables, delimit the two variable names with #. Or use ## to indicate a full factorial (both variables and the interactions).

To create an interaction with a continuous variable, prefix them with c..


See also

Stata manual for -regress-

Stata manual for regress post-estimation


CategoryRicottone

Stata/Regress (last edited 2025-10-24 18:32:48 by DominicRicottone)