Return to course offering list for 118.816

118.816 Advanced Analysis of Epidemiologic Data 1 (30 credits)

This course provides students with advanced skills to undertake analysis of data in the health and biosecurity context. Techniques covered include linear mixed models, spatial techniques, time series and meta-analysis. Students will work with data collected during epidemiological studies with examples and case studies drawn from a range of species including humans, production animals, aquatic species, companion animals, horses wildlife and plants.

Details Details

  • Year: 2017
  • Mode: Internal
  • Semester: Summer School
  • Location: Manawatu Campus
  • Coordinator: Dr Emilie Vallee
  • Subject: Veterinary Science
  • College: College of Sciences

Online component Details

  • Online component: Partially Taught Online - As part of the course is taught online, Broadband access is required. In addition to accessing the Course Guide, students will be required to access core and supplementary digital study resources, contribute to discussion fora and complete online activities and assessment tasks. Core study resources that can be published in print will be supplied to the students who request them. Learn more about Stream, our online learning environment.

Requirements Requirements help

Note: You may enrol in a postgraduate course (that is a 700-, 800- or 900-level course) if you meet the prerequisites for that course and have been admitted to a qualification which lists the course in its schedule.

Special notes

  • SAS software will be used. This course is run block mode - check block offering for course dates.


  • Start Date: Monday 20 November, 2017
  • End date: Saturday 17 February, 2018

Withdrawal dates Requirements help

The last day to withdraw from this course:

  • Without financial penalty: Wednesday 29 November, 2017
  • Without academic penalty: Friday 26 January, 2018

Learning outcomes

Students who successfully complete this course should be able to:

  1. Interpret basic matrix algebra notation and its application to multivariable analysis of correlated data collected in the health and/or biosecurity context.
  2. Conduct an analysis of correlated data with a normally distributed, continuous response and interpret the results in the context of health and/or biosecurity context.
  3. Develop and interpret the outputs from infectious disease state-transition models.
  4. Analyse spatially clustered data collected in the health and/or biosecurity context, generate geographical outputs of results and interpret the results giving consideration to error, bias, confounding and effect modification.
  5. Perform and interpret the results of a quantitative meta-analysis.

Please note: Learning Outcomes are subject to change until the beginning of the semester in which the course is delivered.


During this course, the following assessments will contribute to your final mark.

Assessment Weighting Note
1 Report 30.0%
2 Report 30.0%
3 Report 30.0%
4 Individual Performance/Presentation 10.0%

Please note: Assessment weightings are subject to change until the beginning of the semester in which the course is delivered.

* Specific dates for assessments will be finalised in information provided on Stream at the start of the Course.

Completion requirements

To successfully complete students must obtain a mark of greater than 50% for the assessments.


There are no set texts for this course.

More information...

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