The Graduate Programme for Haematology & OncologyContent:
This course will offer an introduction to the use of a variety of Stata tools that can save time and increase the reproducibility on the way from data to publication.
The course will focus on how to generate output that is as close to the desired result as possible, with a minimal need for post-editing. Depending on the desired output and the complexity of the project this can be achieved with different tools or a combination of tools. Small projects with simple do-files can benefit from a systematic use of log file and dual log files. More complex projects or publications can often benefit from the use of dynamic text. And probably most projects can save time by letting Stata generate the tables and graphs in the right form instead of modifying them afterwards.
The focus will be on introducing tools and providing supervised basic hands-on experience with the tools during exercises and workshop-sessions.
It will be possible for the participants to submit questions/problems prior to the course to modulate the curriculum according to relevant problems.
After the course the participants should have gained knowledge about:
The general use of log fil
The principles and advantages of using dual log
How to store and reuse results from Stata in tables and text
Basic principles for dynamic text illustrated with the both built in commands and packages from SSC
How to easily generate publication ready tables with various content
How to customise all your output graphs from a do-file to fit journal requirements
PhD courses in Biostatistics (e.g. Biostatistics I at SDU or a similar course), some experience working with Stata is an advantage.
Before the course, the participants will be asked to complete a short questionnaire regarding their Stata experience and knowledge about relevant adjacent programming capabilities in order to provide the best match between teaching and expectations.
Participants should bring their own laptop, and Stata should be installed (Stata 14.1 or newer).
Two day, full time course, with lectures and exercises. It is possible to work with data related to your own project.
Selected articles from Stata Journal will be available on SDU e-learn.
PhD fellow Dennis Lund Hansen
Associate Professor, PhD, Sören Möller SDU / OPEN OUH
PhD, Ebad Fardzadeh Haghish, University of Göttingen
Professor, PhD, Ben Jann, University of Bern
ECTS credits: 1,7
The course is free of charge for PhD Students enrolled in Universities that have joined the "Open market agreement".
For other participants there is a course fee of DKK 5146,83,-