Stata Course

Welcome to a new course in the statistical package Stata. The course is aimed at PhD. candidates, Post Doctors and Researchers in Medical Statistics and Epidemiology in general.

Stata is statistical software for data science and an alternative to packages like SPSS, R or SAS. The buzzwords: "Obtain and manipulate data. Explore. Visualize. Model. Make inferences.”

The course is“open” and participants can attend those parts of the course that are of most interest. The upside of this is that there is no fee, no attendance sheets and no exam! The downside is that the course will not give any credits in the Ph.d. program.

The courses will be held on Zoom. If you are interested in joining, please register by clicking on the session link for each of the sessions you plan to attend.

You can find course material (Presentations, Syntax and Data) at the end of this page.

Teachers: Hein Stigum, Jonathan Wörn. 

You can sign up for later sessions at any time before the session.

Register for Individual Sessions – Click on Session Link 

The course will have lectures in 3 levels:

  • Beginner: No previous experience in Stata.
  • Elementary: General knowledge of using Stata (as in the two beginners courses)
  • Advanced: Experience in Stata use (as given by the elementary courses)    

In addition, some experience in data handling and statistical analysis will make understanding easier. We are targeting Ph.d. candidates, Post Doctors and Researchers in Medical Statistics and Epidemiology in general.


The course will have 3 hours of lectures (12:30-15:30) for each theme. No laptops needed. We will give out exercises with solution syntaxes at the end of each lesson. Participants are encouraged to solve these on their own or in groups.


Date Level Theme /Session Link Teacher Venue
16.feb. Beginner

Introduction to STATA: Interface, file types, data handeling, basic commands

Jonathan Wörn Zoom
23.feb. Beginner Graphics: Making plots for data and results Jonathan Wörn Zoom
2.mars Elementary Linear Regression: Standard model, non-linear effects, interactions, effects of outliers, predictions Hein Stigum
9.mars Elementary Logistic regression: Standard model, non-linear effects, interaction, effects of outliers, predictions
Hein Stigum
23.mars Advanced Survival analysis: Flexible Parametric Survival Models Hein Stigum Zoom
30.mars Advanced Automating analysis: Returned results, macros, matrices, loops Hein Stigum Zoom
6.april Advanced Programing: Simulating data for Linear, Logistic and Survival data: Writing programs for Simulation, Bootstrapping and Power Calculations 
Hein Stigum


13.april Advanced Individual fixed effects regression: Examining within-unit changes, controlling for unit-specific characteristics. Setting up data; model specification and interpretaton; graphing results. Jonathan Wörn Zoom


Department of Community Medicine and Global Health.

Contact: Hein Stigum



Published Dec. 16, 2020 10:02 AM - Last modified Apr. 13, 2021 8:59 AM