STATA: A Powerful Tool for Data Analysis

In the fields of economics, public health, and political science, Stata is the undisputed king of statistical software. It combines the ease of a point-and-click interface with the power of a command-line language, making it both accessible and reproducible.

Whether you are cleaning messy survey data or running complex econometric models, Stata provides a robust environment for your research.

If you need help writing do-files or interpreting your output, our data analysis consulting service is here to assist.

What is Stata?

Stata is a general-purpose statistical software package created in 1985 by StataCorp. It is widely used for data manipulation, visualization, statistics, and automated reporting. Unlike R, which is open-source, Stata is a commercial product known for its stability and dedicated support.

The Stata Interface

Stata’s interface has four main windows:

1. Command Window: Where you type your commands.
2. Results Window: Where the output (tables, logs) appears.
3. Review Window: A history of your past commands.
4. Variables Window: A list of all variables in your current dataset.

Pro Tip: Always use a Do-file. This is a text file where you write and save your commands. It ensures your analysis is reproducible and easy to edit later.

Data Management

Stata excels at handling data. Key commands include:

• use filename.dta, clear: Loads a Stata dataset.
• describe: Shows variable names, types, and labels.
• summarize: Provides mean, standard deviation, min, and max.
• generate new_var = ...: Creates a new variable.
• replace var = ... if ...: Modifies an existing variable based on conditions.

Regression Analysis in Stata

Running a linear regression is simple:

regress y x1 x2 x3

Stata also provides powerful post-estimation tools to check assumptions:

• estat hettest: Tests for heteroskedasticity (unequal variance).
• vif: Checks for multicollinearity (correlation between predictors).
• predict residuals, r: Generates residuals for normality checking.

For detailed tutorials, UCLA IDRE’s Stata guide is the gold standard resource.

Panel Data Analysis

One of Stata’s biggest strengths is analyzing Panel Data (data collected from the same subjects over multiple time periods). This allows you to control for unobserved variables that don’t change over time (like a country’s culture).

Common commands include:

• xtset id_variable time_variable: Tells Stata you have panel data.
• xtreg y x, fe: Runs a Fixed Effects model.
• xtreg y x, re: Runs a Random Effects model.

Use the Hausman Test (hausman fixed random) to decide between fixed and random effects.

Get Help with Your Stata Project

Stata’s syntax is logical but strict. A missing comma or misspelled variable can halt your entire analysis. Our team of econometricians and data scientists can help you write clean, efficient code and interpret your results with confidence.