2017/18 Undergraduate Module Catalogue

EPIB3035 Research Methods for Clinical Sciences

10 creditsClass Size: 50

Module manager: Dr Richard Feltbower
Email: r.g.feltbower@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2017/18

Pre-requisite qualifications

Normally successful completion of Year 2 MBChB programme at a UK medical school or equivalent.

Co-requisites

PATH3050

Research Proj in Clinical Sci

This module is not approved as a discovery module

Objectives

The objectives of this module are to:

(1) provide an understanding of study design and research methods as applicable to clinical sciences
(2) provide skills in data presentation and standard statistical analysis of data to support the research project

Learning outcomes
On completion of this module students should be able to:

- classify the different types of research study and distinguish which type to use to address a clinical research question
- evaluate ethical issues relating to research projects
- identify and evaluate potential sources of error and bias in laboratory and clinical research
- critically analyse research results and compile in an appropriate format suitable for publication
- critically apply appropriate standard statistical methods to the analysis of experimental data
- interpret output derived from statistical analyses correctly

Skills outcomes
Appropriate presentation of data in tables and figures
Use of SPSS/Stata for statistical analysis of data.

Syllabus

Students will learn about different types of research study design, the importance of ethics in research, issues such as uncertainty or bias pertinent to both laboratory research and data analysis, how to undertake descriptive analyses, present research data effectively and how to apply statistical methods (tests, regression modelling) to the analysis of data through a series of lectures, tutorials and workshops. In particular, hands on workshops will allow students to practice using standard statistical methods in SPSS or 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
Class tests, exams and assessment	1	3.00	3.00
Lecture	10	1.00	10.00
Practical	2	10.00	10.00
Tutorial	2	2.00	4.00
Independent online learning hours			28.00
Private study hours			45.00
Total Contact hours			27.00
Total hours (100hr per 10 credits)			100.00

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 model data. They will be expected to make use of the module reading list to gain further understanding of the main learning outcomes.

Opportunities for Formative Feedback

Student progress will be monitored through classroom discussion with tutors and through feedback from set tasks. This feedback will be both oral, in the work sessions, and written for practice problems. There will be a formative PC-based practical task and related write-up with results fed back to students before the deadline for the VLE based computer exercise. Some feedback will be through the VLE and there will be a dedicated tutorial near the end of the module for students to communicate comments about the module, its structure and feedback methods and timeliness.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
In-course MCQ	VLE Based	50.00
Computer Exercise	VLE Based	50.00
Total percentage (Assessment Coursework)		100.00

Resits will be of the same format as the original piece of coursework. If a student were to fail one of the coursework assessments but pass another yielding an overall mark of 40 or more, they would still pass the module.

Reading list

The reading list is available from the Library website

Last updated: 08/08/2012

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