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Regression Modelling is a course in biomedical statistics and statistical computing which will provide you with an advanced level of knowledge in key concepts (such as statistical methods for categorical and count outcomes), and introduce you to regression modelling (logistic regression, ordered polytomous regression, models for count data, survival analysis). Statistical modelling is illustrated using the statistical software StataÌý

In terms of knowledge, this module aims to teach you how to select and correctly use statistical regression methods for the analysis of simple datasets using different types of variables. In terms of skills, you should be able to handle data and use statistical software after taking this module. This includes using appropriate tests and methods, creating figures and summaries of results, interpreting statistical results related to specific research questions, and presenting the results in a clear way to non-statisticians.Ìý

In general, this module aims to provide you with:Ìý

1. A basic knowledge of concepts and methods used in statistical modellingÌý

2. The principles of data analysisÌý

3. A foundation on which to build detailed knowledge appropriate to particular research interestsÌý

4. An appreciation of the errors that may arise in the analysis of data in biomedical studiesÌý

5. Experience of solving the problemsÌý

This module is compulsory for students on the MSc/Diploma Social Epidemiology and MSc/Diploma in Dental Public Health. Subject to places being available, the module is also available for other postgraduate students from ¹û¶³Ó°Ôº such as students from MSc Population Health and MSc Global Health and Development. Spaces are limited to 120.Ìý

You will attend 10 half-day sessions in Term 2. The majority of sessions will consist of a lecture (90 minutes) and a related practical computer based exercise (90-120 minutes). There will be approximately equally divided contact hours between theory and computer practical sessions in order to consolidate the concepts learnt by applying them in a variety of contexts relevant to clinical and social epidemiology. All the materials from the lectures will be available on the course Moodle page; datasets for the computer-based seminars, seminar tasks, model answers for the seminars and materials for self-learning will be also available on Moodle. There will also be an FAQ section and on-line discussion maintained on Moodle.Ìý