Medical Statistics with Stata

Postgraduate course

Course description

Objectives and Content


The course will give an introduction to the statistics program STATA and the most basic statistical methods used in medical and epidemiologic research


  • Data management, including generating new variables, merging files and switching between wide and long format
  • Loops and various data management commands in Stata for streamlining work in Stata
  • Stata command syntax
  • Commands for making automatic tables with results from statistical analyses
  • Use of do-files to make the analyses more efficient and document you work and to make reproducible results
  • Use help-files, Stata documentation and online resources
  • Use log-files as documentation of analysis results
  • Descriptive statistics
  • Analysis of continuous variables (t-test, correlation, linear regression)
  • Analysis of categorical variables (chi-square test, Fisher¿s exact test, logistic regression)
  • Survival analysis (Kaplan Meier curves, log-rank test, Cox regression)
  • Graphics in Stata

Learning Outcomes


After completion of the course the student should be able to:

- Manage and analyse data in Stata and interpret results from the most basic statistical methods in medical and epidemiological research


  • After completion of the course the student should be able to:
  • Merge files and generate new variables
  • Import and export datasets from other fil formats
  • Use do-files in an efficient manner and write comments to increase readability
  • Use help files in Stata to write and edit Stata-code and use do-files to structure statistical analyses in order to achieve reproducible results
  • Use descriptive statistics to describe and explore datasets
  • Perform statistical analyses in Staa for continuous and categorical variables (including t-test, correlation, linear regression, cross tables with estimation of risk ratios and odds ratios, logistic regression, Kaplan Meier curves, log-rank test, Cox-regression) and understand the interpretation of effect estimates, p-values and confidence intervals
  • Choose the correct statistical methods based on formulation of problem statements and type and distribution of outcome and exposure variables
  • Make different types of graphs in Stata and edit the graphs to make them ready for publication in scientific journals

Generalized skills

After completion of the course the student should be able to:

  • Understand how a typical statistics program works
  • Have a basis for starting to use other similar programs
  • Understand and interpret analysis results from the most used statistical methods in medical research
  • Be able to analyse their own research data with Stata

Level of Study

Master/ Ph.d.

Semester of Instruction

Autumn and spring
Required Previous Knowledge
Knowledge in medical statistics, MEDSTA, HELSTA or equivalent
Credit Reduction due to Course Overlap
- ELMED313 (2 sp)
Access to the Course

Course registration on Studentweb, deadline 1. September for the autumn and 1st February for the spring semester.

Visiting student at the Faculty of Medicine, deadline: 1st August for the autumn semester and 1st January for the spring semester.

Teaching and learning methods

Lectures and individual practices in STATA with help. Home work.

3 days.

Total hours: 15 hours + home work

Compulsory Assignments and Attendance
- Attendance in class
Forms of Assessment
Written home examination
Grading Scale
Assessment Semester
Autumn and spring