Course catalogue doctoral education - VT22

  • Application can be done between 2021-10-15 and 2021-11-15
Application closed
Title Fundamentals of Stata Language
Course number 5315
Programme Epidemiology
Language English
Credits 1.5
Date 2021-09-13 -- 2021-09-17
Responsible KI department Department of Global Public Health
Specific entry requirements
Purpose of the course This course aims at introducing students to the fundamental elements of the statistical software Stata. Motivating examples arising from health-related research will be used to demonstrate how to use the programming language. Learning activities will give students the possibility to learn Stata the hard yet easier way – that is – problem, code, and run.
Intended learning outcomes After successfully completing this course you as a student should be able to:
- describe quantitative, categorical, and string data
- recode existing variables
- explain how to work with time and space variables
- select an appropriate visualization according to the data
- illustrate how to control and automatize code
- draw random variables from realistic mechanisms
- compare distributions of statistics under repeated sampling
- write do-files for preparing and analysing research data
- create well-structured do-files to facilitate reproducible research
Contents of the course This course is providing the basics to import, and describe common forms of data; create tables of descriptive statistics eventually stratified; generate new variables; recode existing variables; and visualize either empirical data or theoretical data. Advanced topics include define a new function; avoid replication of code by looping; and simulate a plausible data generating mechanism. Learning activities will be based on real or hypothetical studies arising in health-related research.
Teaching and learning activities Lectures, group work, exercises, and individual coding workout using Stata®.
Compulsory elements The individual examination (summative assessment) is compulsory.
Examination Individual written examination. Students who do not obtain a passing grade in the first examination will be offered a second chance to resubmit the examination within two months of the final day of the course. Students who do not obtain a passing grade at the first two examinations will be given top priority for admission the next time the course is offered.
Literature and other teaching material Useful link:
Number of students 8 - 25
Selection of students Eligible doctoral students will be prioritized according to 1) the relevance of the course syllabus for the applicant’s doctoral project (according to written information), 2) date for registration as a doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a short description of current research training and motivation for attending, as well as an account of previous courses taken.
More information The content on how Stata can be used to analyze epidemiological data is not covered in this course. Students should bring their own laptop with a Stata license (any version will do).
Additional course leader
Latest course evaluation Course evaluation report
Course responsible Nicola Orsini
Department of Global Public Health
Contact person Anastasia Urban
Institutionen för global folkhälsa