Course description
This course will stimulate participants to reflect on and perform transparent and reproducible data management of complex quantitative data (i.e., combination of data registers, databases and surveys).The course is aimed at PhD students working with research projects that involve data management of complex data. Ideally, students are either planning or initiating the data management process. Participants must have basic programming skills using either SAS, STATA or R software.
The aim of the course is to improve the course participants’ ability to:
• Apply relevant tools, strategies and methods for transparent and reproducible data management of complex data
• Perform and document data management of complex data
During the course, participants will gain hands-on experience with the research process, from working with a predefined research question to handling raw data and producing an analysis-ready dataset.
Throughout the course, participants will gain hands-on experience with central elements of data management, including metadata, data flow diagrams, documentation, merging multiple datasets, the creation of derived variables, handling of missing data, and data quality control. These elements constitute important content to include in the data management plan.
The course aims to build practical skills in data management through hands-on exercises using SAS, STATA, or R. Participants should bring their own laptop with SAS, STATA or R installed.
On completion of the course, the participant must be able to:
Knowledge• Demonstrate knowledge regarding Danish data infrastructure and data sources.
• Identify different data sources, study units, and data formats (wide versus long data structure) in relation to a specific research question.
• Describe tools for transparent and reproducible data management, including metadata and data flow diagrams.
Skills
• Perform data management of complex data, including merging multiple datasets, the creation of derived variables, handling of missing data, and data quality control in SAS, STATA or R.
• Create a flow chart describing the handling of data during the data management process.
• Document the data management process from raw data to the analysis-ready data set in a data management plan.
Competencies
• Communicate and discuss key tools and methods for transparent and reproducible data management with supervisors and colleagues. • Critically reflect upon the data management process and how decisions made during data management might influence the data analysis and study results.
Teaching methods
There will be lectures and exercises (individually and in smaller groups) with tasks related to examples from register data and the participant´s own project. Participants will receive feedback continuously during the course days.
Course fee:
The course is free of charge for PhD students enrolled in Universities that have joined the "Open market agreement" and NorDoc agreement.
For all other participants the course fee is:
DKK 4000
EUR 353