Linear & Logistic Regression
Subject POPH90144 (2016)
Note: This is an archived Handbook entry from 2016.
Credit Points: | 12.5 | ||||||||||||
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Level: | 9 (Graduate/Postgraduate) | ||||||||||||
Dates & Locations: | This subject has the following teaching availabilities in 2016: July, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here. | ||||||||||||
Time Commitment: | Contact Hours: 30 hours Total Time Commitment: 170 hours | ||||||||||||
Prerequisites: | Subject Study Period Commencement: Credit Points: OR Subject Study Period Commencement: Credit Points: | ||||||||||||
Corequisites: | None | ||||||||||||
Recommended Background Knowledge: | Special computer skills required: Students are expected to have experience using the Stata statistical package | ||||||||||||
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. |
Coordinator
Assoc Prof Julie SimpsonContact
Melbourne School of Population and Global Health
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Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: enquiries-STEM@unimelb.edu.au
Future Students:
- Further Information: http://mspgh.unimelb.edu.au/
- Email: Online Form
Subject Overview: |
This subject is compulsory for students doing a Master of Epidemiology or a Master of Science – Epidemiology. The subject covers linear regression methods for continuous outcome variables and logistic regression methods for binary outcome variables. The subject equips students with the practical skills to apply these regression methods to data from epidemiological studies using the statistical package Stata. Also covered is how to adjust for confounding and investigate effect modification using regression models. The focus is on the practical interpretation of the measures of association estimated by these regression models.
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Learning Outcomes: |
On completion of this subject, students are expected to:
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Assessment: |
A written assignment of not more than 8 pages due at the start of the 4th week of the subject (30%), a written assignment of not more than 10 pages due two weeks after the intensive delivery period (40%) and a 1.5-hour open-book examination (administered by the School) to be held during the examination period at the end of semester 2 (30%). |
Prescribed Texts: | BR Kirkwood and JAC Sterne, Essential Medical Statistics Second Edition, Blackwell Science, 2003. |
Breadth Options: | This subject is not available as a breadth subject. |
Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
Generic Skills: |
Upon completion of this subject, students will have developed skills in:
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Links to further information: | http://www.mspgh.unimelb.edu.au |
Notes: |
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Related Course(s): |
Master of Epidemiology Master of Public Health Master of Science (Epidemiology) |
Related Majors/Minors/Specialisations: |
Electives in the Master of Veterinary Public Health (Emergency Animal Disease) Environment and Public Health Epidemiology and Biostatistics Gender and Women's Health Health Economics and Economic Evaluation Public Health Tailored Specialisation Tailored Specialisation |
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