Stata FAQ
Can I make regression tables that look like those in journal articles?
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 findit outreg (see How can I used the findit command to search for programs and get additional help? for more information about using findit).
Let's illustrate use of the outreg command using the high school and beyond data file we use in our Stata Classes.
use http://www.ats.ucla.edu/stat/stata/notes/hsb1, clear
(highschool and beyond (200 cases))
We will run 3 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 we suppress the variable labels and indicate we want to replace test.doc if it already existed.
outreg using test.doc, nolabel 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, appending these results to the previous ones in test.doc.
outreg using test.doc, nolabel append
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, nolabel append
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.We have manually adjusted the spacing to show the columns properly.
(1) (2) (3)
read read read
write 0.646 0.328 0.114
(10.47)** (4.72)** (1.58)
math 0.520 0.296
(7.38)** (3.98)**
science 0.266
(4.10)**
socst 0.281
(4.83)**
Constant 18.162 7.542 2.002
(5.49)** (2.31)* (0.63)
Observations 200 200 195
R-squared 0.36 0.50 0.58
Absolute value of t-statistics in parentheses
* significant at 5% level; ** significant at 1% level
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