EPM5004 Linear models
Faculty of Medicine, Nursing and Health Sciences
EPM5004 Linear models is a level 5, 6-credit-point, postgraduate unit from the Faculty of Medicine, Nursing and Health Sciences, offered in 2021 in Semester 1 and Semester 2 at Alfred Hospital. It needs EPM5002, EPM5014 and MPH5040 and unlocks 8 units.
- Credit points
- 6
- Offered in 2021
- Semester 1, Semester 2
- Alfred Hospital
- Assessment
- No exam
- 2 tasks
The 2027 handbook has no page for EPM5004. This is its 2021 entry, the latest one.
Reviews
No reviews yetNo reviews yet. Be the first to review EPM5004.
Requisites
Before EPM5004
Prerequisites
Pass these before you enrol.
Corequisites
Pass these before, or take them in the same semester.
After EPM5004
8 units list EPM5004 as a prerequisite or corequisite.
- EPM5006Clinical biostatisticsNo reviews yetCoreq
- EPM5008Longitudinal and correlated data analysisNo reviews yet
- EPM5009Categorical data and generalised linear modelsNo reviews yetCoreq
- EPM5010Survival analysisNo reviews yet
- EPM5011Biostatistics practical project: double unitNo reviews yet
- EPM5012BioinformaticsNo reviews yet
- EPM5013Bayesian statistical methodsNo reviews yet
- EPM5015Biostatistics practical project: single unitNo reviews yet
Enrolment rules
Overview
This unit explores biostatistical applications of linear models with an emphasis on underlying theoretical and computational issues, practical interpretation and communication of results. By a series of case studies, students explore extensions of methods for group comparisons of means (t-tests and analysis of variance) to adjust for confounding and to assess effect modification/interaction, together with the development of associated inference procedures. Multiple regression strategies and model selection issues will be presented together with model checking and diagnostics. Nonparametric regression techniques, and random effects and variance components models will also be outlined.
Offerings in 2021
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Alfred Hospital | De |
| Second semester | Alfred Hospital | De |
Assessment
- 2 x Written assignments (30% each)60%
- Practical exercisesThreshold hurdle40%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Understand the major theoretical and computational issues underlying analyses based on linear models.
- 2
Develop appropriate regression modelling strategies based on unit matter considerations, including choice of models, control for confounding and appropriate parameterisation.
- 3
Be proficient at using a statistical software package (e.g. Strata) to perform multiple regression and analysis of variance.
- 4
Understand the construction, use and interpretation of regression modelling diagnostics.
- 5
Express the results of statistical analyses of linear models in language suitable for communication to medical investigators or publication in biomedical or epidemiological journal articles.
- 6
Appreciate the role of modern techniques including non-parametric smoothing and variance components models.
Learning resources
Required resources
See Moodle for details about required resources.
Contacts
- Unit Coordinators
- Professor Stephane Heritier
- Chief Examiners
- Professor Stephane Heritier
Common questions
What are the prerequisites for EPM5004?
You need EPM5002, EPM5014 and MPH5040 before you enrol; and EPM5003 before or alongside it. Enrolment rules also apply.
What can I take after EPM5004?
EPM5004 is a prerequisite or corequisite for 8 units, including EPM5006, EPM5008, EPM5009, EPM5010, EPM5011 and EPM5012.
When is EPM5004 offered?
In 2021, EPM5004 runs in Semester 1 and Semester 2 at Alfred Hospital.
Does EPM5004 have an exam?
No. EPM5004 has 2 assessment tasks and no exam.
More details
- Credit points
- 6
- Level
- 5
- Study level
- Postgraduate
- Faculty
- Faculty of Medicine, Nursing and Health Sciences
- Organisational unit
- Department of Epidemiology and Preventive Medicine
- Type
- Coursework
- EFTSL
- 0.125
- Student contribution
- SCA Band 2
- Study abroad
- Not available
- Handbook years
- 20202021