Longitudinal and Correlated Data

Subject POPH90123 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: None
Total Time Commitment:

170 hours

Prerequisites:
  • POPH90014 Epidemiology 1 OR POPH90016 Epidemiology
  • POPH90148 Probability and Distribution Theory
  • MAST90100 Inference Methods in Biostatistics OR POPH90017 Principles of Statistical Inference
  • MAST90102 Linear Regression OR POPH90120 Linear Models
  • MAST90099 Categorical Data: Models and Methods OR POPH90121 Categorical Data & GLMs
Corequisites:

None

Recommended Background Knowledge:

None

Non Allowed Subjects:

None

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.
The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website.

Coordinator

Prof John Carlin

Contact

john.carlin@unimelb.edu.au

Melbourne School of Population and Global Health

OR

Currently enrolled students:

Future Students:

Subject Overview:

Topics covered: Paired data; the effect of non-independence on comparisons within and between clusters of observations; methods for continuous outcomes: normal mixed effects (hierarchical or multilevel) models and generalised estimating equations (GEE); role and limitations of repeated measures ANOVA; methods for discrete data: GEE and generalized linear mixed models (GLMM); methods for count data.


Learning Outcomes:

To enable students to apply appropriate methods to the analysis of data arising from longitudinal (repeated measures) epidemiological or clinical studies, and from studies with other forms of clustering (cluster sample surveys, cluster randomised trials, family studies) that will produce non-exchangeable outcomes.

Assessment:
  • Two major assignments due in week 7 and end of semester (30% each)
  • Five short assignments (approx 3 hours of work each) due throughout the semester (8% each)
Prescribed Texts:

None

Recommended Text:
Fitzmaurice G, Laird N, Ware J. Applied Longitudinal Analysis. John Wiley and Sons, 2004. (ISBN 978-0-471-21487-8)

Resources Provided to Students: Printed course notes and assignment material by mail, email, and online interaction facilities.

Special Computer Requirements: Stata and SAS statistical software

Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:
  • Independent problem solving;
  • facility with abstract reasoning;
  • clarity of written expression;
  • sound communication of technical concepts.
Links to further information: http://www.mspgh.unimelb.edu.au
Notes:

This subject is not available in the Master of Public Health.

Related Course(s): Graduate Certificate in Biostatistics
Graduate Diploma in Biostatistics
Master of Biostatistics
Postgraduate Diploma in Biostatistics

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