Stata is a general-purpose statistical software package.

Commands

The commands stata, stata-se, and stata-mp run Stata in command-line mode. The stata command is the "standard version", and stata-se is the "special edition", which has larger limits. These are both single-core programs.

The stata-mp command uses multiple CPU cores, which might be faster for some scenarios. By default, it will use all cores available on the host. This behavior can be controlled using the Stata set processors command.

There are corresponding commands xstata, xstata-se, and xstata-mp that will start Stata in GUI mode. In order for this to work, you must use X forwarding, as described in How-to Run an X11 application.

Local Details

The current license is limited to three users. Please be sure to exit the program when you are done.

When running stata-mp, it's important match the SLURM resource request to the number of cores used by stata-mp. For the default behavior (use all cores), use the SLURM --cpus-per-task flag to request the cores. See How-to Submit an OpenMP Job for an example of this in a batch script, or How-to Start an Interactive Job for an interactive session.

Documentation

Stata Website – Documentation – Wikipedia

Usage Examples

Hello World

$ module load stata

$ cat helloworld.do
/* stata hello world program */

program define hello
	di "Hello World"
end

hello

$ stata -b do helloworld.do

$ ls
helloworld.do  helloworld.log

$ less helloworld.log
.
.
.

. do helloworld.do 

. /* stata hello world program */
. 
. program define hello
  1.         di "Hello World"
  2. end

. 
. hello
Hello World

. 
end of do-file

Simple Regression

Given an input file auto.do

auto.do

sysuse auto

regress price weight mpg

regress price weight mpg foreign

run the command

stata -b do auto.do

which gives the result in auto.log

auto.log

. do auto.do

. sysuse auto
(1978 Automobile Data)

.
. regress price weight mpg

      Source |       SS       df       MS              Number of obs =      74
-------------+------------------------------           F(  2,    71) =   14.74
       Model |   186321280     2  93160639.9           Prob > F      =  0.0000
    Residual |   448744116    71  6320339.67           R-squared     =  0.2934
-------------+------------------------------           Adj R-squared =  0.2735
       Total |   635065396    73  8699525.97           Root MSE      =    2514

------------------------------------------------------------------------------
       price |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      weight |   1.746559   .6413538     2.72   0.008      .467736    3.025382
         mpg |  -49.51222   86.15604    -0.57   0.567    -221.3025     122.278
       _cons |   1946.069    3597.05     0.54   0.590    -5226.245    9118.382
------------------------------------------------------------------------------

.
. regress price weight mpg foreign

      Source |       SS       df       MS              Number of obs =      74
-------------+------------------------------           F(  3,    70) =   23.29
       Model |   317252881     3   105750960           Prob > F      =  0.0000
    Residual |   317812515    70  4540178.78           R-squared     =  0.4996
-------------+------------------------------           Adj R-squared =  0.4781
       Total |   635065396    73  8699525.97           Root MSE      =  2130.8

------------------------------------------------------------------------------
       price |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      weight |   3.464706    .630749     5.49   0.000     2.206717    4.722695
         mpg |    21.8536   74.22114     0.29   0.769    -126.1758     169.883
     foreign |    3673.06   683.9783     5.37   0.000     2308.909    5037.212
       _cons |  -5853.696   3376.987    -1.73   0.087    -12588.88    881.4934
------------------------------------------------------------------------------

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