Introductory Analysis of Linked Data

Introductory Analysis of Linked Data

Tuesday, January 23, 2018

Introductory Analysis of Linked Data - The University of Sydney

This 5-day short course introduces the topic of the analysis of linked data at an introductory to intermediate level. It acquaints health services researchers, clinical practitioners and managers with the theory and skills needed to analyse linked health data. The modular structure of the course provides participants with a theoretical grounding on each theme, followed by a hands-on practical exercise in our computer lab each day, using de-identified linked NSW data files.

The course is suitable for people with no previous experience in the analysis of linked health data. However, it does assume familiarity with introductory statistical and epidemiological methods, as taught, for example, in a Master of Public Health degree course. The computing component of the unit also assumes a basic familiarity with computing syntax used in SAS and methods of basic statistical analysis of fixed-format data files. Participants must have this assumed knowledge.

Semester 1: Monday 25 June – Friday 29 June 2018

Semester 2: Monday 12 November – Friday 16 November 2018

Applications for the June short course must submitted by Friday 8 June 2018, and for the November short course by Friday 26 October 2018. Places are strictly limited so book early to avoid disappointment.

Please email the Application Form to: Your application will then be assessed; If approved, you will be emailed a link to make an online payment; Once payment has been received, your place in the course is secure. The 2018 fee for the short course is approximately $3,800 including GST.



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Data linkage has a significant role in reduction of cervical cancer in Australia. The HPV vaccine was introduced in 2007, success of the vaccine was monitored by linking vaccine registers to cervical smear registers in Queensland & Victoria.

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Please note our Christmas and New Year office shutdown days and times for the Program Office and the rest of our data linkage infrastructure. We wish you a Merry Christmas and a Happy New Year!