Postgraduate Course: Advanced Epidemiology (PUHR11112)
|School||Deanery of Molecular, Genetic and Population Health Sciences
||College||College of Medicine and Veterinary Medicine
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
|Course type||Online Distance Learning
||Availability||Not available to visiting students
|Summary||This 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.
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: challenges of more complex data sets and studies; risk prediction; missing data; causal inference and directed acyclic graphs
Course Delivery Information
|Academic year 2022/23, Not available to visiting students (SS1)
|Course Start Date
|Learning and Teaching activities (Further Info)
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
|Assessment (Further Info)
|Additional Information (Assessment)
||Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
The summative assessment will include components of critical appraisal and data interpretation.
||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
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of a range of advanced epidemiological theories, concepts and principles
- Extend the understanding of statistics software to apply appropriate methods to a range of advanced epidemiological problems and interpret results
- Critically evaluate the application of advanced epidemiological methods in existing literature and your own research
- Communicate complex ideas and arguments
|Reading lists will be provided in the course handbook|
|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
|Keywords||epidemiology,applied epidemiology,missing data,causal inference,risk prediction
|Course organiser||Dr Regina Prigge
|Course secretary||Miss Lucy Courage
Tel: (0131 6)51 7111