Stata


Stata is a general-purpose statistical software package developed by StataCorp for data manipulation, visualization, statistics, and automated reporting. It is used by researchers in many fields, including biomedicine, economics, epidemiology, and sociology.
Stata was initially developed by Computing Resource Center in California and the first version was released in 1985. In 1993, the company moved to College Station, Texas and was renamed Stata Corporation, now known as StataCorp. A major release in 2003 included a new graphics system and dialog boxes for all commands. Since then, a new version has been released once every two years. The current version is Stata 19, released in April 2025.
WWW Official Site

Technical overview and terminology

User interface

From its creation, Stata has always employed an integrated command-line interface. Starting with version 8.0, Stata has included a graphical user interface which uses menus and dialog boxes to give access to many built-in commands. The dataset can be viewed or edited in spreadsheet format. From version 11 on, other commands can be executed while the data browser or editor is opened.

Data structure and storage

Until the release of version 16, Stata could only open a single dataset at any one time. Stata allows for flexibility with assigning data types to data. Its compress command automatically reassigns data to data types that take up less memory without loss of information. Stata utilizes integer storage types which occupy only one or two bytes rather than four, and single-precision rather than double-precision is the default for floating-point numbers.
Stata's proprietary output language is known as SMCL, which stands for Stata Markup and Control Language and is pronounced "smickle".
Stata's data format is always tabular in format. Stata refers to the columns of tabular data as variables.

Data format compatibility

Stata can import data in a variety of formats. This includes ASCII data formats and spreadsheet formats.
Stata's proprietary file formats have changed over time, although not every Stata release includes a new dataset format. Every version of Stata can read all older dataset formats, and can write both the current and most recent previous dataset format, using the saveold command. Thus, the current Stata release can always open datasets that were created with older versions, but older versions cannot read newer format datasets.
Stata can read and write SAS XPORT format datasets natively, using the fdause and fdasave commands.
Some other econometric applications, including gretl, can directly import Stata file formats.

History

The development of Stata began in 1984, initially by William Gould and later by Sean Becketti. The software was intended to compete with statistical programs for personal computers such as SYSTAT and MicroTSP. Written in the C programming language, Stata was released for MS-DOS in 1985 with 44 commands. Since then, versions of Stata have been released for systems running Unix variants like Linux distributions, Windows, and MacOS. All Stata files are platform-independent.
appenddirinfileplotspool
beepdoinputquerysummarize
bydroplabelregresstabulate
captureeraselistrenametest
confirmexitmacroreplacetype
convertexpandmergerunuse
correlateformatmodifysave
countgeneratemoreset
describehelpoutfilesort

There have been 19 major releases of Stata between 1985 and 2025 and additional code and documentation updates between major releases. In its early years, extra sets of Stata programs were sometimes sold as "kits" or distributed as Support Disks. With the release of Stata 6 in 1999, updates began to be delivered to users via the web.
Hundreds of commands have been added to Stata in its 37-year history. Certain developments have proved to be particularly important and continue to shape the user experience today, including extensibility, platform independence, and the active user community.

Extensibility

The program command was implemented in Stata 1.2, giving users the ability to add their own commands. ado-files followed in Stata 2.1, allowing a user-written program to be automatically loaded into memory. Many user-written ado-files are submitted to the Statistical Software Components Archive hosted by Boston College. StataCorp added an ssc command to allow community-contributed programs to be added directly within Stata. More recent editions of Stata allow users to call Python scripts using commands, as well as allowing Python IDEs like Jupyter Notebooks to import Stata commands. Although Stata does not support R natively, there are user-written extensions to use R scripts in Stata.

User community

A number of important developments were initiated by Stata's active user community. The Stata Technical Bulletin, which often contains user-created commands, was introduced in 1991 and issued six times a year. It was relaunched in 2001 as the peer-reviewed Stata Journal, a quarterly publication containing descriptions of community-contributed commands and tips for the effective use of Stata. In 1994, a listserv began as a hub for users to collaboratively solve coding and technical issues; in 2014, it was converted into a web forum. In 1995, Statacorp began organizing user and developer conferences that meet annually. Only the annual Stata Conference held in the United States is hosted by StataCorp. Other user group meetings are held annually in the United States, the UK, Germany, and Italy, and less frequently in several other countries. Local Stata distributors host User Group meetings in their own countries.
VersionRelease dateSelect new or enhanced features
1.0January 1985
  • Initial release
  • Forty-four commands
1.1February 1985
  • Bug fixes
    • 1.2May 1985
  • New menu system
  • Better online helpkeep
    • 1.3August 1985
  • Stata/Graphicsprogram
    • 1.4August 1986
  • New documentation
  • Formatted infile
    • 1.5February 1987anova, logit, probit
    2.0June 1988
  • New graphics
  • String variables
  • Survival analysis: Cox and Kaplan-Meier
  • Stepwise regression
    • 2.1September 1990
  • Byte variables
  • Factor analysis
  • ado-filesreshape
    • 3.0March 1992logistic, ologit, oprobit, clogit, mlogit, tobit, cnreg, rreg, qreg, weibull, ereg, epitab, pweights
    3.1August 1993mvreg, sureg, heckman, nlreg, areg, canon, nbreg
  • constrained linear regressionml, codebook
    • 4.0January 1995xtreg, glm
    5.0October 1996xtgee, xtprobit, prais, newey, intreg
  • survey estimation commandsfracpoly, st extended
    • 6.0January 1999
  • web aware
  • new ml
  • time-series operatorsarima, arch, st rewritten
    • 7.0December 2000frailty, xtabond
  • cluster analysisnlogit, roc
  • SMCL
    • 8.0January 2003
  • graphics
  • extended GUI, dialog boxes available for all commandsmanova
  • more survey
  • more time series
  • more GLLAMM internalization
    • 8.1July 2003
  • updated ml
    • 8.2October 2003
  • graphics changes
    • 9.0April 2005
  • mata matrix programming language
  • survey features
  • linear mixed models
  • multinominal probit models
    • 9.1September 2005
    9.2April 2006
    10.0June 2007
  • graph editor
  • logistic and Poisson models with complex, nested error components
    • 10.1August 2008
    11.0July 2009
  • factor variablesmargins postestimation command
  • multiple imputation
    • 11.1June 2010
    11.2March 2011
    12.0July 2011
  • automatic memory management
  • structural equation modeling
    • 12.1January 2012
    13.0June 2013
  • long strings
  • treatment effects
    • 13.1October 2013
    14.0April 2015
  • unicode support
  • Bayesian statistical analysis
    • 14.1October 2015
    14.2September 2016
    15.0June 2017
  • latent class analysis
  • PDF and Word documents
  • color transparency or opacity in graphs
    • 15.1November 2017
    16.0June 2019
  • frames
  • lasso regression
  • automated reporting
  • updated choice models
    • 16.1February 2020
    17.0April 2021
  • updated tables command
  • bayesian econometrics
    • 18.0April 2023
  • Bayesian model averaging
  • causal mediation analysis
  • heterogeneous difference-in-differences

    • Software products

    There are four builds of Stata: Stata/MP, Stata/SE, Stata/BE, and Numerics by Stata. Whereas Stata/MP allows for built-in parallel processing of certain commands, Stata/SE and Stata/BE are bottlenecked and limit usage to only one single core. Stata/MP runs certain commands about 2.4 times faster, roughly 60% of theoretical maximum efficiency, when running parallel processes on four CPU cores compared to SE or BE versions. Numerics by Stata allows for web integration of Stata commands.
    SE and BE versions differ in the amount of memory datasets may utilize. Though Stata/MP can store 10 to 20 billion observations and up to 120,000 variables, Stata/SE and Stata/BE store up to 2.14 billion observations and handle 32,767 variables and 2,048 variables respectively. The maximum number of independent variables in a model is 65,532 variables in Stata/MP, 10,998 variables in Stata/SE, and 798 variables in Stata/BE.
    The pricing and licensing of Stata depends on its intended use: business, government/nonprofit, education, or student. Single user licenses are either renewable annually or perpetual. Other license types include a single license for use by concurrent users, a site license, volume single user for bulk pricing, or a student lab.

    Example code

    The following set of commands revolve around simple data management.

    sysuse auto // Open the included auto dataset
    browse // Browse the dataset
    describe // Describes the dataset and associated variables
    summarize // Summary information about numerical variables
    codebook make foreign // Summary information about the make and foreign variables
    browse if missing // Browse only observations with missing data for variable rep78
    list make if missing // List makes of the cars with missing data for variable rep78

    The next set of commands move onto descriptive statistics.

    summarize price, detail // Detailed summary statistics for variable price
    tabulate foreign // One-way frequency table for variable foreign
    tabulate rep78 foreign, row // Two-way frequency table for variables rep78 and foreign
    summarize mpg if foreign 1 // Summary information about mpg if the car is foreign
    by foreign, sort: summarize mpg // As above, but using the "by" prefix.
    tabulate foreign, summarize // As above, but using the tabulate command.

    A simple hypothesis test:

    ttest mpg, by // T-test for difference in means for domestic vs. foreign cars

    Graphing data:

    twoway // Scatter plot showing relationship between mpg and weight
    twoway, by // Three graphs for domestic, foreign, and all cars

    Linear regression:

    generate wtsq = weight^2 // Create a new variable for weight squared
    regress mpg weight wtsq foreign, vce // Linear regression of mpg on weight, wtsq, and foreign
    predict mpghat // Create a new variable contained the predicted values of mpg
    twoway, by // Graph data and fitted line