This FAQ illustrates the outreg
command that makes regression tables in a format that is commonly used in
journal articles. The outreg
command was written by John Luke Gallup and appears in the
Stata
Technical Bulletin #49. You can download outreg from within Stata by
typing search outreg (see
How can I use the search command to search for programs and get additional
help? for more information about using search).
Let’s illustrate use of the
outreg
command using the high school and beyond data file we use in our Stata Classes.
use https://stats.idre.ucla.edu/stat/stata/notes/hsb1, clear (highschool and beyond (200 cases))
We will run three regression models predicting
the variable read. The first model will predict from the variable
write, the second model will predict from math and write,
and the third model will predict from socst, math, and write.
We will use outreg to create a single table that will summarize
these models side by side.
regress read write
Source | SS df MS Number of obs = 200
---------+------------------------------ F( 1, 198) = 109.52
Model | 7450.28755 1 7450.28755 Prob > F = 0.0000
Residual | 13469.1324 198 68.0259215 R-squared = 0.3561
---------+------------------------------ Adj R-squared = 0.3529
Total | 20919.42 199 105.122714 Root MSE = 8.2478
------------------------------------------------------------------------------
read | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
write | .64553 .0616832 10.465 0.000 .5238896 .7671704
_cons | 18.16215 3.307162 5.492 0.000 11.64037 24.68394
------------------------------------------------------------------------------
Here we use outreg to capture the
results from the prior model, storing the output in the file test.doc
and indicate we want to replace test.doc
if it already existed.
outreg using test.doc, replace
Now we run our second regression model.
regress read math write
Source | SS df MS Number of obs = 200
---------+------------------------------ F( 2, 197) = 96.80
Model | 10368.63 2 5184.31501 Prob > F = 0.0000
Residual | 10550.79 197 53.5573096 R-squared = 0.4956
---------+------------------------------ Adj R-squared = 0.4905
Total | 20919.42 199 105.122714 Root MSE = 7.3183
------------------------------------------------------------------------------
read | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
math | .5196538 .0703972 7.382 0.000 .380825 .6584826
write | .3283984 .0695792 4.720 0.000 .1911828 .4656141
_cons | 7.541599 3.26819 2.308 0.022 1.096471 13.98673
------------------------------------------------------------------------------
We run outreg again to capture the results
of the second model, merging these results to the previous ones in test.doc.
outreg using test.doc, merge
Now we run our third regression model.
regress read science socst math write
Source | SS df MS Number of obs = 195
---------+------------------------------ F( 4, 190) = 65.23
Model | 11608.8938 4 2902.22346 Prob > F = 0.0000
Residual | 8453.08565 190 44.4899245 R-squared = 0.5787
---------+------------------------------ Adj R-squared = 0.5698
Total | 20061.9795 194 103.412265 Root MSE = 6.6701
------------------------------------------------------------------------------
read | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
science | .2657521 .0648044 4.101 0.000 .1379236 .3935806
socst | .2808959 .0581116 4.834 0.000 .1662691 .3955227
math | .2961578 .0743467 3.983 0.000 .1495068 .4428087
write | .1141745 .0724559 1.576 0.117 -.0287468 .2570959
_cons | 2.001966 3.163988 0.633 0.528 -4.239088 8.243021
------------------------------------------------------------------------------
We run outreg again to capture the results
of the third model.
outreg using test.doc, merge
The contents of test.doc look like
those below. Tabs are used between columns to get the columns to line
up, so you will need to adjust your tab settings to get the tables to look as
you desire.
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* p<0.05; ** p<0.01