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DRPS : Course Catalogue : Deanery of Molecular, Genetic and Population Health Sciences : Public Health Research

Postgraduate Course: Advanced Epidemiology (PUHR11112)

Course Outline
SchoolDeanery of Molecular, Genetic and Population Health Sciences CollegeCollege of Medicine and Veterinary Medicine
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis course will introduce a broad range of advanced epidemiological concepts and explore quantitative methods required for the interpretation and conduct of epidemiological studies. This course will be of particular relevance to students with a good grasp of quantitative methods who plan to undertake epidemiological research.
Course description The Advanced Epidemiology course introduces students to a broad range of advanced epidemiological concepts beyond those taught in introductory and intermediate courses, and enables students to undertake critical evaluations of advanced quantitative methods used in epidemiological studies, and to apply these methods in their own research.

Topics covered include: missing data; counterfactual approach to causation; directed acyclic graphs; diagnostic testing and risk prediction.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Intermediate Epidemiology (PUHR11067) OR Statistical Modelling for Epidemiology (PUHR11064) OR Data analysis with R (PUHR11103) OR
Prohibited Combinations Other requirements If not these specific courses, students should have some experience in epidemiology and statistics; they should also have some familiarity with R.
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) Quota:  None
Course Start Flexible
Course Start Date 05/08/2023
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 5, Seminar/Tutorial Hours 1, Online Activities 35, Feedback/Feedforward Hours 5, Formative Assessment Hours 5, Revision Session Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 46 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %

The summative assessment will include two components: (1) Critical appraisal of a paper on a topic covered in this course and (2) interpretation of R output.
Feedback Weekly course content will include practical exercises/ activities. Students will receive feedback via model answers and discussion groups for peer-support with feedback from tutors and course organisers, if needed.

There will be one formative assessment with personalized feedback from tutors and course organisers.

Detailed written feedback will be provided via Learn after the summative assessment.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate a critical understanding of a range of advanced epidemiological theories, concepts and principles
  2. Extend the understanding of statistics software to apply appropriate methods to a range of advanced epidemiological problems and interpret results
  3. Critically evaluate the application of advanced epidemiological methods in existing literature and your own research
  4. Communicate complex ideas and arguments
Reading List
Reading lists will be provided in the course handbook
Additional Information
Graduate Attributes and Skills The following generic and transferable skills are expected to be developed during this course:

1) Generic cognitive skills

Students will learn to apply critical analysis, evaluation and synthesis to a variety of issues, or issues that are informed by developments in epidemiology.

Students will learn to critically review, consolidate and extend knowledge, skills, practices and thinking in relation to epidemiology.

Students will also learn to manage complex epidemiological issues and make informed judgements in situations in the absence of complete or consistent data/information.

2) Communication, numeracy and IT skills

Students will learn to communicate with peers, senior colleagues and specialists through the tutorials, group work and assessment.

Students will be encouraged to use a wide range of ICT applications to support and enhance work at this level and adjust features to suit purpose.

Students will undertake critical evaluations of a range of numerical and graphical data through the tutorials and assessment.

3) Autonomy, accountability and working with others

Students will be encouraged to exercise substantial autonomy and initiative in professional and equivalent activities.

Students will take responsibility for their own work
Keywordsepidemiology,applied epidemiology,missing data,causal inference,risk prediction,diagnostic testing
Course organiserDr Regina Prigge
Course secretaryMiss Lucy Courage
Tel: (0131 6)51 7111
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