Linear Models

Subject POPH90120 (2012)

Note: This is an archived Handbook entry from 2012.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2012:

Semester 2, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Distance

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: None
Total Time Commitment: 8-12 hours total study time per week
Prerequisites: -

Subject
Study Period Commencement:
Credit Points:
Semester 1, Semester 2
12.50
Semester 1, Semester 2
12.50
Semester 1, Semester 2
12.50
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

Professor John Carlin, Melbourne School of Population Health, University of Melbourne
Professor Andrew Forbes, Monash University

Biostatistics Collaboration of Australia
Email: bca@ctc.usyd.edu.au
Website: www.bca.edu.au

OR

Academic Programs Office
Melbourne School of Population Health
Tel: +61 3 8344 9339
Fax: +61 3 8344 0824
Email: sph-gradinfo@unimelb.edu.au

Subject Overview:

The method of least squares; regression models and related statistical inference; flexible nonparametric regression; analysis of covariance to adjust for confounding; multiple regression with matrix algebra; model construction and interpretation (use of dummy variables, parameterisation, interaction and transformations); model checking and diagnostics; regression to the mean; handling of baseline values; the analysis of variance; variance components and random effects.

Objectives: To enable students to apply methods based on linear models to biostatistical data analysis, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results.
Assessment: Two case study assignments to be submitted during semester worth 35% and 40% respectively (approx 12 hours work each).
Submission of selected practical exercises throughout the semester worth 20% in total (approx 10 hrs of work)
Contribution to online quizzes worth 5% (approx 6 hrs of work)
Prescribed Texts:

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

Special Computer Requirements: Stata statistical software

Recommended Texts:

Kutner MH, Nachtsheim CJ, Neter J, Li W. Applied Linear Statistical Models. 5th edition. McGraw-Hill/Irwin 2005. ISBN 978-0-07-310874-2
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.sph.unimelb.edu.au
Notes:

This subject is not available in the Master of Public Health.
Related Course(s): Master of Biostatistics
Postgraduate Certificate in Biostatistics
Postgraduate Diploma in Biostatistics

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