Australian Institute of Health and Welfare - Investigating Bias in Data Linkage Results

An opportunity to help improve data analysis regarding Australia's health and welfare.

label Opportunity type

Student opportunity type

College approved Internship
schedule Application date
Applications open/close
27 Mar 2024 | 9am - 2 Apr 2024 | 11:59pm
school Level

Degree level

Bachelor
Master

About

The Australian Institute of Health and Welfare (AIHW) provides reliable, regular and relevant information and statistics on Australia’s health and welfare.

We are committed to providing high quality, national data and analysis across the health, housing and community services sectors. This covers a wide range of areas, from health and welfare expenditure, hospitals, disease and injury, disability and mental health, to ageing, disadvantaged and vulnerable populations, homelessness, and Indigenous health and welfare.

Project: Investigating Bias in Data Linkage Results

Internship details

Internship Availability

Winter 2024

Internship Discipline/s

  • Applied math
  • Statistics
  • Data analysis
  • Data linkage

Internship Level

3rd year undergraduate and postgraduate coursework preferred

Available to International Students

Yes

Preferred Project Skills:

  • Statistical analysis
  • Statistical analysis software experience (Python, SAS, R)
  • SQL

Clearances Required

Police check

Host Supervisor

Elena Ougrinovski

E: elena.ougrinovski@aihw.gov.au

T: 02 6244 1147

Location

1 Thynne St

Bruce, ACT

Summary

The Institute’s Data Linkage Unit undertakes probabilistic data linkage of many of Australia’s key health and welfare datasets to enable analysis of service pathways and outcomes by policy analysts. This probabilistic data linkage is undertaken using in-house data linkage software (SAS-based DALI), which the AIHW is currently considering replacing with a new off-the-shelf solution (Python based SPLINK). These software solutions are based on differing algorithms. This project would involve gaining an understanding of these key differences and investigating the impact of them on linkage outputs.

Note: if you wish to apply for this project, list it as a preference under the 'Other' category in your Expression of Interest form and email Science.Internships@anu.edu.au.