Which Stata

[Saurabh Cloudas]

Itlooks like the primary diff across versions is the size of the datasets they are geared toward. That's good to know. Judging from this info, I also am thinking Stata IC should serve my needs well.

My main concern was that some versions wouldn't allow me to use various stata modules that have come in handy in the past. For example, Arne Hole's modules for mixed logit and hetero conditional logit models (Arne Risa Hole). My impression is that these modules will work on any version of stata. Is this your impression as well?

Students from another department in my country use gretl. It's free, and it's a bit friendlier than Stata, I think. From what I was told you don't have to write the commands (is this true?). I haven't looked at it yet, though.

Nearly every international student I know has pirated software. It disheartens me to know that if their computers ever become audited (which happens regularly on university and corporate owned machines) that they could be held liable. Visas can be revoked, friends.

Do NOT get "Small Stata." Some of my undergrad students bought that (against my advice) when I taught econometrics and they could not run several examples from the class textbook (Wooldridge's Introductory Econometrics).

Stata/IC is okay for most things you will do in the first and second year. You will almost never reach the number of maximum variables that require SE. With that said, you could eventually end up doing projects that use a lot of dummy variables or fixed effects and, if you don't drop variables, you might reach the limit.

Stata/MP is overkill as you begin your career. I use it now because work off a server and parallel processing saves an incredible amount of time (what took me a weekend or more with SE can be done in a few hours with MP).

As you all begin your career, you will notice that many computers are being built now with multiple cores and 64-bit operating systems. The basic versions of Stata do not support these advances. You will be limited to 1000MB (1GB) or a little less depending on how your system memory is running. This can be inconvenient and slow you down a lot. For now, not a big deal, but keep in mind that you may want to upgrade.

For Stata newbies, search the Statalist Archives if you have questions (or type "help Stata -cmd-" into Google) and look at the official blog. The manuals are online for the latest version, 11.0. Look into picking up a copy of StatTransfer if you plan to work between statistical programs or to collaborate with others.

Don't get anything smaller than IC. I got an IC perpetual license, and it gets the job done most of the time, but it's limits are binding sometimes. Usually, as wdoerner said above, it happens if you're doing work with lots of fixed effects, group-specific time trends, etc. The number of variables can rise pretty fast. Buying SE may be worth it if you're confident you're going to be doing this type of applied micro work with big datasets. But that won't come until you're doing your own research.

Actually, my company is offering a course on R that I will be taking in a couple of weeks. I'm very excited as i've heard good things about it and, of course, it is a free alternative to programs like STATA.

It's a sweet thing to know, and very helpful. But, as with everything, you have to learn it, and you gottawanna. You can do virtually everything with Stata, R, or Matlab, but not as relatively easy as with Python.

The following table shows general guidelines for choosing a statisticalanalysis. We emphasize that these are general guidelines and should not beconstrued as hard and fast rules. Usually your data could be analyzed inmultiple ways, each of which could yield legitimate answers. The table belowcovers a number of common analyses and helps you choose among them based on thenumber of dependent variables (sometimes referred to as outcome variables), thenature of your independent variables (sometimes referred to aspredictors). You also want to consider the nature of your dependentvariable, namely whether it is an interval variable, ordinal or categoricalvariable, and whether it is normally distributed (see What is the difference between categorical, ordinal and interval variables?for more information on this). The table then shows one or morestatistical tests commonly used given these types of variables (but notnecessarily the only type of test that could be used) and links showing how todo such tests using SAS, Stata and SPSS.

*Technically, assumptions of normality concern the errors rather than the dependent variable itself. Statistical errors are the deviations of the observed values of the dependent variable from their true or expected values. These errors are unobservable, since we usually do not know the true values, but we can estimate them with residuals, the deviation of the observed values from the model-predicted values. Additionally, many of these models produce estimates that are robust to violation of the assumption of normality, particularly in large samples.

Stata is a general-purpose statistical software package with an easy-to-use graphic (point-and-click) user interface. Stata also allows advanced users to perform data analysis tasks using a command language.

If you would like to install Stata on your PC or Mac, individual Stata licenses are available at an academic discount for USC faculty, staff, and students. You may purchase Stata software directly from StataCorp. in College Station, Texas. For more information on ordering Stata, including shipping and download information, see the following links on the Stata website:

StataCorp offers different versions of Stata. You may choose the version that is right for you depending on the size of the datasets you will be analyzing. For more details on the different versions of Stata, visit www.stata.com/products/which-stata-is-right-for-me.

Stata (/ˈsteɪtə/,[2] STAY-ta, alternatively /ˈsttə/, occasionally stylized as STATA[3][4]) 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.[5]

Stata was initially developed by Computing Resource Center in California and the first version was released in 1985.[6] In 1993, the company moved to College Station, Texas and was renamed Stata Corporation, now known as StataCorp.[1] A major release in 2003 included a new graphics system and dialog boxes for all commands.[6] Since then, a new version has been released once every two years.[7] The current version is Stata 18, released in April 2023.[8]

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.

Until the release of version 16,[9] 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 (4 bytes) rather than double-precision (8 bytes) is the default for floating-point numbers.

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.[10] Thus, the current Stata release can always open datasets that were created with older versions, but older versions cannot read newer format datasets.

The development of Stata began in 1984, initially by William (Bill) Gould and later by Sean Becketti. The software was originally intended to compete with statistical programs for personal computers such as SYSTAT and MicroTSP.[6] Stata was written, then as now, in the C programming language, initially for PCs running the DOS operating system. The first version was released in 1985 with 44 commands.[6]

There have been 17 major releases of Stata between 1985 and 2021, and additional code and documentation updates between major releases.[7] 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.[6] The initial release of Stata was for the DOS operating system. Since then, versions of Stata have been released for systems running Unix variants like Linux distributions, Windows, and MacOS.[6] All Stata files are platform-independent.

Hundreds of commands have been added to Stata in its 37-year history.[11][12] 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.[6]

The program command was implemented in Stata 1.2, giving users the ability to add their own commands.[6][13] 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.[14] 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.[15] Although Stata does not support R natively, there are user-written extensions to use R scripts in Stata.[16]

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