2023/24 Taught Postgraduate Module Catalogue
MEDP5321M Research Methods
15 creditsClass Size: 30
Module manager: Prof Richard Feltbower
Email: r.g.feltbower@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2023/24
This module is mutually exclusive with
| EPIB3035 | Research Methods for Clinical Sciences |
This module is not approved as an Elective
Objectives
This module is designed to prepare you to carry out your research project later in the degree programme.The module is also designed to allow you to make judgements about the quality of the peer reviewed literature base, to understand the concepts of research and data analysis and how to present and interpret appropriate information derived from statistical analysis.
Learning outcomes
On completion of this module students should be able to:
- Understand the philosophy of Evidence Based Practice
- Understand the main statistical tools used in clinical research, for i) evaluation of the work of others and ii) analysis of your own results
- Design appropriate experiments/studies and adopt the appropriate statistical methods for evaluation
- Use Stata software to process data appropriately and carry out statistical analysis proficiently.
- Critically assess and review published work
Understand how to apply causal inference methods and identify confounding for observation data.
Skills outcomes
Appropriate presentation of data in tables and figures
Use of Stata for statistical analysis of data.
Ability to critically assess and review published work.
Syllabus
- Introduction to the philosophy of evidence based practice
- Basic statistical techniques
- Design of experiments/studies
- Quality assessment of published work
- Critical assessment and review of published work
- Introduction to causal inference methods and Directed Acyclic Graphs (DAGs) for observational data.
In particular, hands on workshops will allow students to practice using standard statistical methods in Stata and interpreting their output in order to prepare them for the types of statistical analysis they may need in their research projects.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 8 | 1.50 | 12.00 |
| Practical | 6 | 2.00 | 12.00 |
| Tutorial | 3 | 1.50 | 4.50 |
| Independent online learning hours | 55.00 | ||
| Private study hours | 66.50 | ||
| Total Contact hours | 28.50 | ||
| Total hours (100hr per 10 credits) | 150.00 | ||
Private study
Students will work on example problems and scenarios to practice presentation and the summarising of data conveyed in tables and figures, read medical journal papers to identify study type and examples of good and bad practice in data presentation, and practice statistical analysis of data. They will be expected to make use of the module reading list to gain further understanding of the main learning outcomes.Self-directed reading will cover other additional research methods which may be appropriate to their own Research Project such as ROC analysis, survival analysis, or dealing with repeated measures (longitudinal data) and missing data.
Opportunities for Formative Feedback
Student progress will be monitored through classroom discussion with tutors and through feedback from Stata practical questions. This feedback will be both oral, in the work sessions, and written for practice problems. Some feedback will be through the VLE/Minerva and there will be a dedicated Stata drop-in session and revision tutorial near the end of the module for students to clarify any questions they may have and to communicate comments about the module.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Essay | Critical Appraisal | 30.00 |
| Total percentage (Assessment Coursework) | 30.00 | |
Resits will be of the same format as the original piece of coursework. Compensation is permitted between the assessments
Exams
| Exam type | Exam duration | % of formal assessment |
| Online Time-Limited assessment | 3 hr 00 mins | 70.00 |
| Total percentage (Assessment Exams) | 70.00 | |
Exam will be in the form of an online, open book, assessment. Duration 48-hours with an expected completion time of 3-hours or less.
Reading list
The reading list is available from the Library websiteLast updated: 09/08/2023
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- Undergraduate module catalogue
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