Linear Models

Subject POPH90120 (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

Semester 2, Parkville - Taught online/distance.
Pre-teaching Period Start not applicable
Teaching Period 25-Jul-2016 to 23-Oct-2016
Assessment Period End 18-Nov-2016
Last date to Self-Enrol 05-Aug-2016
Census Date 31-Aug-2016
Last date to Withdraw without fail 23-Sep-2016

This subject is only available to students who are currently enrolled in the Graduate Diploma or Master of Biostatistics and whose enrolment in that course commenced prior to 2016.



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

170 hours
Prerequisites:

POPH90017 may be taken concurrently.

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:

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

Assoc Prof Julie Simpson

Contact

julieas@unimelb.edu.au

Melbourne School of Population and Global Health

OR

Currently enrolled students:

Future Students:

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.
Learning Outcomes:

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:
  • 2 x written assignments (requiring approx 10 hours of work each) due in week 7 & 8 (30% each)
  • 4 x practical exercises (approximately 3 hours of work each) including brief online quizzes due throughout the semester (10% each)
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): Graduate Certificate in Biostatistics
Postgraduate Diploma in Biostatistics

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