Advanced quantitative research methods can provide robust evaluative evidence about the causal effects of intervention choices. In this module, you’ll be introduced to a range quantitative research methods that are commonly used within applied health research including secondary (meta-analysis) and primary methods (i.e. cohort studies, case control, etc.). You’ll also learn about the techniques of trial design and the role and importance of discrete projects for ‘proof of concept’, feasibility, efficacy, and effectiveness studies. You will consider a range of research designs, strategies and quantitative techniques (e.g., univariate and introductory multivariate statistics). You’ll be taught to identify how to prepare data for analysis. You’ll evaluate the strengths and weaknesses of different key study designs and will design a study demonstrating the use of one of the methods introduced in the module. By the end of this module, you will have become a ‘critical consumer’ of research with the knowledge and understanding necessary to evaluate quantitative research appropriately.
Lecture 8 hrs
Seminar 16 hrs
Workshop 8 hrs
Available ONLY for the MSc Applied Health and Care Research as an optional module
Group Project Report 2000 words 50% weighting
Report - Critique of a published quantitative study 2,000 words 50% weighting
Reassessment Method:
Like –for-like
The most up to date reading list for each module can be found on the university's reading list pages.
On successfully completing the module, students will be able to:
Systematically understand, at an advanced level, quantitative methods commonly used in current health and care research and their relationship to the hierarchy of research methods.
Appraise and have a comprehensive understanding of the most common forms of bias in health and social care research.
Critically evaluate and compare quantitative research methods in health and care with respect to their design, analysis and interpretation.
Systematically and critically apply these techniques using widely available statistical software tools.
Critically communicate the results of quantitative research clearly, correctly, and with integrity to specialist and non-specialist audiences
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