Short Course

Introduction to Data Linkage for Research

Overview

This short course, run by the School of Population and Global Health at The University of Melbourne, provides an introduction to administrative data and data linkage. The course is designed for policy makers, researchers, managers, analysts, and others working in the public sector with an interest in generating evidence. No knowledge of data linkage is required; however, basic familiarity with research methods is an asset. On completion of this course, participants will have a basic understanding of the practical considerations involved in using administrative data, and an awareness of the lifecycle of linked data research.

Specifically, this course will discuss the application of linked administrative data to real world problems, and outline how data linkage can be used to provide valuable, policy-relevant evidence.

  • Date/Time: This course, generally run annually, will next be held online over two half days on dates to be set. Times provisionally are from 10am to 2.30pm AEST/ AEDT (Melbourne, Sydney, Canberra) on both days. For other time zones, use World Clock Meeting Planner available here.
  • Location: Online via Zoom
  • To book: Click the Apply Now button on this page to email the course administrator to be placed on a wait list for the next course. Once the 2024 date has been set, a Book Now button will be accessible on this page for you to register and make payment.

Note: For groups of 10 people or more, this course can be tailored to your organisation's needs and delivered online, or on site at your workplace depending on your location.

EOI for course participation:  If you wish to express interest to undertake this course, please contact the course administrator at linkage-shortcourse@unimelb.edu.au .  You will be then be placed on a wait list for the next course date.

Course outline

Module 1: Administrative Data and Data Linkage In this module you will gain an understanding of the diverse types of administrative data that can potentially be used for research. You will learn what data linkage is, and gain a basic understanding of how data can be linked for research purposes. We will explore some of the strengths and limitations of using linked administrative data for research, including some of the key practical and methodological considerations associated with data linkage. The session will conclude with some examples of research using linked data, and discussion of how these studies have informed policy or practice.

Module 2: Acquiring Data In this module we will introduce the key concepts involved in scoping the data required to answer a question of interest. The module will introduce design concepts such as bias, censoring, sampling and missingness, and you will learn how to critically appraise administrative data resources. The module will cover practical considerations such as ethics and privacy principles, and will provide an overview of a typical data acquisition process.

Module 3: Data Management In this module we will provide an overview of the data management process as it relates to linked data. This will include an overview of data management principles and relevant legal and data security frameworks. We will discuss the basic manipulation of data, including identifying the layout of your data, methods of transferring between long and wide formats, and considerations when combining datasets. We will detail the basics of data security followed by advice on setting up data analysis sessions to maximise the transferability and repeatability of research studies. Finally, we will discuss some common pitfalls of linked data, focusing on free-text, coded and date-time variables.

Module 4: Generating and Communicating Results This module will provide an overview of the unique considerations involved in generating and communicating results from linked administrative data. The module will introduce common approaches and techniques for the analysis of linked data, and the reasoning behind them. We will provide an overview of data analysis techniques commonly applied to big data, and common strengths and limitations associated with analysis of linked data. The module will introduce practical ways of communicating results that maximise impact beyond the research sector, and equip you with the basic knowledge to engage with and contribute to data linkage research.

Course leaders

Prof Stuart Kinner

Dr Jesse Young

How much is it?

Course Fees

Early bird rate – $500 (+GST=$550)
Non-early bird (regular) rate – $550 (+GST=$632.50) 
Student rate – $250 (+GST =$275) for a limited number of places for registrants who are current students.

A Zoom Meeting link will be emailed to you prior to the course date. Participants will be given access to course e-materials during and after completion of the course for a finite period. A certificate of completion will also be provided.

Note:  This course may be cancelled prior to the course date if it has not reached the minimum number of participants. Registration fees will be reimbursed.

Application procedure

  • Payment is by card via the University’s eCommerce shopfront.  A link to the shopfront will be provided on this page once the date/s for the 2024 course/s have been set.

If your organisation needs an invoice for payment, please request via email to linkage-shortcourse@unimelb.edu.au

  • Registration is via the University's eCommerce shopfront when payment is made.
  • Further enquiries, or to express interest in this course: linkage-shortcourse@unimelb.edu.au

Melbourne School of Population and Global Health
The University of Melbourne
VIC  3010  Australia

Course Information

Calendar

Key dates

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2024 - Date/s TBA

Course is held over two half days

Dollar

Fees

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Early bird: $500 (+ GST=$550)

Non-early bird (regular) rate: $575 (+GST=$632.50)

Student rate: $250 (+GST=$275). Limited places available at this rate for current students

Location

Location

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Online via Zoom

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Entry requirements

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No knowledge of data linkage is required; however, basic familiarity with research methods is an asset.