PU5054: ADVANCED QUANTITATIVE METHODS AND ANALYSIS FOR PSYCHOLOGY (2022-2023)

This course teaches students in the field of health psychology how to conduct high quality quantitative research and how to think and operate within a professional, ethical framework. The structure of the course reflects the logical flow of the research process itself, moving week on week from the planning of research (generating and refining research questions, evaluating evidence, designing studies), through study conduct (ethical practice, quantitative methods, measurement issues, data handling, research governance) to the statistical analysis, interpretation, reporting and dissemination of research findings (to academic, policy, public, and media audiences).

Aims of the Course: This course aims to equip students with the skills and capabilities to use a range of quantitative research methods and analytic techniques within a professional, ethical framework.

At the end of the course, students will be able to;

1. Identify and critically appraise the features of different research designs, data collection methods, analytic techniques and dissemination approaches
2. Select appropriate study designs and analysis methods for different research questions and data types
3. Generate novel material (e.g. research questions, hypotheses, questionnaire items, etc) that reflect understanding of key research principles
4. Apply relevant ethical and professional practice frameworks to research and practice scenarios, identifying potential issues and generating strategies to minimise or avoid them
5. Prepare and analyse complex data sets using advanced quantitative statistics, accurately interpreting and reporting the results
6. Tailor research outputs so that they conform to published guidelines and are suitable for different audiences (e.g. public, stakeholder, academic)

The topics covered by the course

• The research process (including critical appraisal, the scientific method, generating research questions)
• Research design (including experimental, quasi-experimental, randomised, case-control, cohort, longitudinal, cross sectional, n-of-1, evidence synthesis)
• Sources of bias in design, data collection and analysis; strategies to tackle this bias
• Research ethics and governance, professional codes of practice
• Questionnaire design, construction and psychometrics
• Data preparation and exploration, dealing with awkward data (missing data, transformation, etc)
• Sampling and sample sizes
• Diary methods, ecological momentary assessment, n of 1
• Working with existing data (secondary data, linked data, routine data etc)
• Advanced quantitative analysis (ANOVA, multiple regression, logistic regression, multi-level modelling)
• Research dissemination (academic, policy, public)
• Reporting research in line with published standards, guidelines and recommendations

Information on contact teaching time is available from the course guide.

More Information about Week Numbers

There are no assessments for this course.