Epidemiology & Analytic Methods 2

Subject POPH90143 (2011)

Note: This is an archived Handbook entry from 2011.

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

This subject has the following teaching availabilities in 2011:

April, Parkville - Taught on campus.
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

Block

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 4 hours/wk (weeks 7-12)
Total Time Commitment: Students will be expected to undertake additional tasks, reading and preparation equivalent to a total additional time commitment of 80 to 90 hours.
Prerequisites: -
Subject
Study Period Commencement:
Credit Points:
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

Assoc Prof Julie Simpson

Contact

Centre for Molecular, Environmental, Genetic and Analytic (MEGA) Epidemiology
Tel: +61 3 8344 0732
Email: julieas@unimelb.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: This subject consolidates the basic principles covered in “Epidemiology and Analytic Methods I” and develops a more substantial understanding of epidemiological research, and in particular of the key concepts of confounding, information bias, stratification and statistical inference. Students are introduced to analytic methods for comparison of two means and two proportions, to stratified analysis to control confounding and tests for effect modification using the Stata statistical software package.
Objectives: On completion of this subject, students are expected to:
  • Be able to calculate, apply and interpret the fundamental measures of association used in epidemiology
  • Understand what confounding is and how to assess its presence
  • Be able to perform stratified analyses for the control of confounding
  • Know when and why standardisation is used and how to perform it
  • Understand what effect modification is and how to assess its presence
  • Be able to compute and interpret p-values and confidence intervals for comparing means and proportions
  • Understand how information bias arises and its effect on study validity
  • Be able to adjust measures of association for measurement error
  • Be able to use Stata for the manipulation and analysis of epidemiological datasets
Assessment:

One assignment of up to 1000 words (25%) due in week 9 or 10
One assignment of up to 2,000 words (35%) due a few weeks after the end of coursework
A 2 hour examination (40%) to be held in the University examination period
Prescribed Texts: Webb P, Bain C & S Pirozzo Essential Epidemiology. Cambridge University Press: 2005, and
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:

On completion of this subject, students are expected to:

  • Develop basic problem solving and analytical skills
  • Develop the epidemiological frameworks to recognise and describe research methods
  • Become familiar with the language and terminology used in epidemiology
  • Develop skills in written communication including basic methods for statistical summary and description of epidemiological data
  • Develop the ability to plan and prioritise reading and assessment tasks

Special computer skills required: Students are expected to have experience using the Stata statistical package for data managements and basic descriptive statistics.

Links to further information: http://www.sph.unimelb.edu.au
Notes:

Related Majors/Minors/Specialisations: Public Health

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