Training

There are various training courses available to support administrative data research, some are essential to access data and others build relevant skills.

Working with Administrative Data Training

If you are a first time researcher, we recommend a free online modular course offered by Centric as a first step. This course provides a good overview of best research practice in the use of administrative data.

For those researchers looking for more additional training, we would encourage them to consider the courses listed below, that are comprehensive introductions and overviews of working with administrative data. Each course varies in length, cost and depth so please enquire directly to each training provider for full details.

1. Introduction to Administrative Data Research and Analysis (IADRA)​ course

This course gives a full introduction to administrative data, describing what it is, some particular problems that may arise in working with this type of data and how to deal with them.

Theoretical sessions and hands-on practical sessions using R syntax and synthetic data from the Scottish Longitudinal Study (SLS) explain to users how to:

  • tidy, clean and recode data
  • link datasets
  • manipulate data
  • conduct data visualisation
  • identify data quality issues
  • and fit regression models

Data showcases and researcher experience sessions describe how to access data and avoid common pitfalls. We always welcome feedback from previous attendees, and here are a few recommendations. The first is from a researcher who attended the course in 2023 (previous course name was An introduction to data science for administrative data research IDS-ADR):

I’d like to also express my thanks to you and the IDS-ADR team. I’ve really enjoyed being in the course, found the help and support incredibly useful and am sorry it is ending. Please pass on sincere gratitude to all of your team.

The second was from a past attendee of the IDS-ADR training course in 2020/2021 (renamed in 2024 as IADRA) - find out why they gave it a 5 star rating!

The IADRA training online course usually runs twice a year, in Spring and Autumn - please see details for future course dates here. 

 

2. Administrative Data Training - Centric

Centric’s online self-guided course is for researchers interested in or currently working with UK administrative data and was co-produced by researchers and stakeholders using administrative data.

The online training via Moodle contains interactive slides and learning materials covering topics such as an introduction to administrative data;  safeguarding public data and working with the public. 

Supporting these modules is an extensive resources section for further reading and to advance understanding. Please visit the Centre for Trials Research at Cardiff University or Centric's webpage for further details on training courses available. 

 

3. Datacise Open Learning

Datacise Open Learning provides precision training for data science in research. It aims to provide world-class, flexible and innovative training for a range of data science disciplines. 

To view their range of courses covering administrative data and linked data, please visit their website or email them at contact@dataciseopenlearning.org.

 

4. Data Awareness Training – The Health Foundation & Cancer Research UK

This course starts with the basics of different types of data, why some is more sensitive and legally protected, and how different access processes are required for different types of data. Further information is given on data access processes and creating safe outputs (Statistical Disclosure Control) from The Health Foundation’s secure data environment.

Please visit the Working Group for Safe Data Access Professionals webpage for further details, where the Slides from this course are available.

 

5. Analysis of Linked Health Data (introductory and advanced) – Swansea University / University of Sydney

These in depth courses are ideal for health and social care researchers, social scientists, clinical practitioners and health care managers and introduce the topic of linked health data analysis at an introductory to intermediate level. 

Practical exercises using deidentified data use programs such as SPSS, SAS, STATA or R to investigate methods of basic statistical analysis. Topics include:

  • Introduction to data linkage and its history 
  • How record linkage works & quality
  • Ethics, data security, application processes 
  • Types of population health databases 
  • Constructing study populations 
  • Arrays, merging datasets, tagging records, creating sequence variables 
  • Measures of health care utilisation; health care episodes 
  • Preparing data for analysis & accuracy and reliability of data sources 
  • Introduction to survival analysis and Cox regression 

Please visit the Data Science webpage at Swansea University for further information on either the Analysis of Linked Health Data (PMIM302) or the Advanced Analysis of Linked Health Data (PMIM602) course, or visit the University of Sydney Short Courses webpage.

Skills Training

Researchers 

Researchers using administrative data need a variety of skills. Training required depends on their experience, the data accessed and the analysis required.

Before researchers can access any data in the National Safe Haven, they must have successfully completed appropriate training, such as the ONS Safe Researcher Training course (ONS-SRT). Specific data controllers have specific training course requirements, so please do check with your Data Controller or Research Coordinator, that they are satisfied the ONS-SRT course is right for your needs.

Research Methods

For those new to quantitative research, most universities run in-depth introductions for staff and students to statistical packages like R, Stata and SPSS.

Output checking/Statistical Disclosure Control (SDC)

Feedback welcome

We welcome feedback. Have you found any useful courses that we should promote? Are there skills where you need training but have not found suitable provision? Please contact us by emailing scadr@ed.ac.uk with your thoughts.