Stata is an interactive data analysis program which runs on a variety of platforms.
Stata is installed on the Windows machines and Macs in OIT's public
clusters and on the Windows machines in the DSS Data Lab.
- How can I get my data into Stata?
- Using Stat/Transfer. Most common transfers are from SPSS/SAS to Stata.
- From ASCII data. Use this link for resources when data is not in any propietary format
(fixed-record form). A codebook or data layout is needed.
- From Excel. Stata 12+ can read Excel files directly. In Stata go to File->Import->Excel (make sure to check 'import first row as variable
- From Excel. Stata 11 or older you can either copy-and-paste. Or save
the excel file as
csv and import it using 'insheet'.
- Getting Started in Data Analysis. Stata tutorial to get started in
data analysis (log file, set memory, describe and summarize data, frequencies, crosstabulations, descriptive statistics, scatterplots, histograms, recoding, renaming and creating
new variables, merge, append and more), converting data from SPSS/SAS/Excel to Stata.
- Reshape. Reshaping data using an example from World Development Indicators (a
commonly used dataset for macro level data)
- Merge/append data
- Running Stata on Unix. Running Unix Stata in text mode, Stata for Unix with an X-Windows interface, running large
jobs in the background
- Linear regresssion. Tutorial on interpreting the outcome of linear
regression, interactions and diagnostics: heteroskedasticity, functional form, predicted values, omitted-variable test,
multicollinearity, outliers, normality, coefficients table (estto/esttab). Include how to present the regression output using
outreg2 (in Word and Excel)
- Interpreting Stata Regression Output. Review of regression, R squared,
- Using Dummy variables in a regression model
- Creating dummy variables.
- Event studies with Stata. Cleaning the data, calculating the event window, estimating normal
performance, calculating the abnormal and cumulative abnormal returns, testins for significance.
- Descriptive statistics. Descriptive statistics using
Stata, Excel and R.
- Fixed/random effects (panel data). Stata tutorial on panel data
analysis showing fixed effects, random effects, hausman tests, test for time fixed effects, Breusch-Pagan Lagrange multiplier,
contemporaneous correlation, cross-sectional dependence, testing for heteroskedasticity, serial correlation, unit roots
- Time series. Tutorial on setting the data as time series, use of lag
operators, subsetting, interpreting correlograms, unit roots, cointegration, QLR or sup-Wald test, Granger causality, Chow test,
test for serial correlation
- Logit/ordered logit regression. Tutorial on interpreting logit
regression output and ordered logit regression output, odds ratios and estimation of probabilities.
- Factor analysis. Tutorial on factor analysis, predicting and
- Multilevel analysis. Tutorial on multilevel analysis: varying
intercept, varying coefficient model, varying slope model and postestimation
- Marginal effects, predicted probabilities. Predicted probabilities and marginal effects after (ordered) logit/probit using margins in Stata
- Differences-in-differences. A basic approach to d-i-d method
- Making nice output tables. Tutorial on using --outreg2-- to report regression output, descriptive statistics, frequencies and basic
- From NLS investigator to Stata
This page was last updated on Jan 6, 2010