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Linear & Logistic Regression (POPH90144)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
Contact information
July
Melbourne School of Population and Global Health
OR
Currently enrolled students:
- General information: https://ask.unimelb.edu.au
- Email: Contact Stop 1
Future Students:
- Further Information: MSPGH Website
- Email: Enquiry Form
Overview
| Availability | July |
|---|---|
| Fees | Look up fees |
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.
Intended learning outcomes
On completion of this subject, students are expected to:
- Recognise when it is appropriate to use linear and logistic regression models
- Demonstrate practical skills in fitting linear and logistic regression models in the statistical computing package, Stata.
- Interpret the measures of association (mean differences and odds ratios) estimated by linear and logistic regression models.
- Describe and demonstrate how to adjust for confounding and identify variables that modify measures of association using these regression methods.
Generic skills
Upon completion of this subject, students will have developed skills in:
- Critical thinking and analysis,
- Finding, evaluating and using relevant information,
- Problem-solving,
- Written communication,
- Using computers.
Last updated: 3 November 2022