ECPR

Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”

ECPR

Install the app

Install this application on your home screen for quick and easy access when you’re on the go.

Just tap Share then “Add to Home Screen”

Back to Panel Details
Back to Panel Details

Introduction to Stata

Diana Schacht
diana.schacht@uni-bamberg.de

University of Bamberg

Diana is a research fellow on the ORA projekt Pathways. She is also Deputy Women's Representative of the Social Sciences faculty at the University of Bamberg, and a Mentee on the feRNet program at the Chair of Sociology (Social Stratification). 

Her research interests include processes of migration and integration, social inequality, and quantitative methods.


Course Dates and Times

Friday 22 February 13:00–15:00 and 15:30–18:00

Saturday 23 February 09:00–12:30 and 14:00–17:30

Prerequisite Knowledge

  • No previous knowledge of Stata required
  • Basic statistical knowledge is assumed (e.g. descriptive statistics, basics of regression analysis)
  • Knowledge of syntax-based software (e.g. SPSS, R) helpful but not required

This course introduces standard statistical procedures in Stata. It does not give detailed insight into the statistical procedures and underlying mathematics.


Short Outline

The course is an add-on to content-based courses. It introduces how Stata works and how it can be used to conduct descriptive, bivariate and multivariate analyses. The course does NOT give detailed insight into statistical techniques or modelling.

By the end of this course, you will be able to use basic Stata commands, and understand 'how Stata does things' well enough to use it for your own analyses.

This course cannot cover all Stata commands and procedures, but will focus on frequently used methods. However, since the basic logic is similar for all Stata commands, you will be able to transfer the knowledge gained to your own project.

Tasks for ECTS Credits

1 credit (pass/fail grade). Attend at least 90% of course hours, participate fully in in-class activities, and carry out the necessary reading and/or other work prior to, and after, class.


Long Course Outline

This course is suited to students who have no experience with Stata, but who bring in basic statistical skills, e.g. some knowledge of descriptive, bivariate and multivariate statistics.

Its aim is to show how Stata can be best used to conduct statistical analyses. Stata relies strongly on the command line interface. Thus, the course gives an insight to general construction of Stata code (syntax). The instructor and teaching assistant will help you to write clear and parsimonious Stata commands, and improve do-files and do-file documentation.

You will learn to use do-files as a simple lab-book, where annotations and ideas can be recorded in addition to the raw code, and to facilitate replicable analyses.

First, we introduce the software package:

  • What is it?
  • What does the Stata interface look like?
  • How does it work?

To demonstrate, we give an applied overview of the various screens and windows.

We then move on to data management (importing and exporting data from various sources, recoding variables and labels, generating new variables), uni- and bivariate statistics.

On Saturday morning, we will cover the basics of regression models.

Depending on the specific interests of participants, the Saturday afternoon session will focus on more advanced topics, such as variations of regression models (e.g. logistic regression), graphs and tables of results, and loops and macros.

Day Topic Details
Friday Introduction: Stata windows, basics of syntax, a first look at a dataset, importing data
  • Why Stata?
  • Organising the Stata screen
  • Basics of Stata syntax
  • Developing a workflow routine
  • Do- and log-files
  • How to import and export data
  • Basic commands for data management: generate, replace, recode, label
  • Basic commands for uni- and bivariate analysis: tabulate, summarize, tabstat, correlate, test
Saturday morning Basics of regression
  • Basics of regression
  • Brief overview of post-regression diagnostics
  • Interaction terms and factor variables
Saturday afternoon Regression models

Depending on the interest of the participants, session may contain (but cannot cover all of the topics):

  • Logit models and/or other types of regression models
  • Introduction to loops and macros
  • Publishable graphs and tables
Day Readings
Friday

Kohler/Kreuter, Data Analysis Using Stata, Third Edition Chapters 1-5, 7, 11

Saturday morning

Kohler/Kreuter, Data Analysis Using Stata, Third Edition Chapter 9

Saturday afternoon

Will be announced depending on choice of participants

Software Requirements

Stata, version 12 or higher.

Literature

ACOCK, A. C. 2016. A Gentle Introduction to Stata, Fifth Edition, College Station, Tex, Stata Press.

KOHLER, U. & KREUTER, F. 2012. Data Analysis Using Stata, Third Edition, College Station, Tex, Stata Press.

LONG, J. S. 2009. The Workflow of Data Analysis Using Stata, College Station, Tex, Stata Press.

MITCHELL, M. N. 2010. Data Management Using Stata: A Practical Handbook, College Station, Tex, Stata Press.

MITCHELL, M. N. 2012. A Visual Guide to Stata Graphics, Third Edition, College Station, Tex, Stata Press.

POLLOCK, P. H. 2015. A Stata Companion to Political Analysis, Third Edition, Washington, D.C, CQ Press College.


Additional Information

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed in due time.

Note from the Academic Conveners

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, contact the instructor before registering.