Stata Course

Welcome to a new course in the statistical package Stata. The course is aimed at Ph.d. 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 at “Frederik Holst hus”. If you are interested in joining, please register by ticking a box for each of the sessions you plan to attend, as there are limited spaces. 

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

Teachers: Hein Stigum, Cecilie Dahl, Nina Iszatt.

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

Sign-up Individual Sessions

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  Teacher Venue
21.jan. Beginner

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

Cecilie Dahl Room 218, Frederik Holsts hus
28.jan. Beginner Graphics: Making plots for data and results Nina Iszatt Room 079, Frederik Holsts hus
4.feb Elementary Linear Regression: Standard model, non-linear effects, interactions,effects of outliers, predictions Hein Stigum
Room 123, Frederik Holsts hus
11.feb Elementary Logistic regression:Standard model, non-linear effects, interaction, effects of outliers, predictions
Nina Iszatt
Room 123, Frederik Holsts hus
18.feb Advanced Survival analysis: Flexible Parametric Survival Models Hein Stigum Room 123, Frederik Holsts hus
25.feb Advanced Automating analysis: Returned results, macros, matrices, loops Hein Stigum Room 123, Frederik Holsts hus
3.mars Advanced Programing: Simulating data for Linear, Logistic and Survival data; Writing programs for Simulation, Bootstrapping and Power Calculations 
Hein Stigum

Room 218

Fredrik Holsts hus



Department of Community Medicine and Global Health.

Contact: Hein Stigum


Publisert 10. okt. 2019 08:24 - Sist endret 2. mars 2020 12:52