Applied Statistics for Health Research

This module aims to provide students with knowledge and critical understanding of standard and advanced quantitative statistical methods within the context of epidemiological and clinical research in humans.

This module is a practical, skills-focused course designed to develop your ability to design, critically analyse, interpret and report the findings of a complex research project in a health-related topic. A large part of the module is structured around a scenario of an outbreak investigation, applying methodologies appropriate for complex surveys and observational cohort/case-control studies. The module will also examine methodologies relevant for randomised controlled clinical trials, as well as applications to spatial analysis and to meta-analysis used for evidence synthesis. The module will concentrate on the practical application of different experimental design strategies and on the interpretation of the results of statistical analysis methodologies, rather than on any detailed mathematical derivations.

Teaching sessions typically comprise an introductory presentation describing a specific type of study design or statistical methodology, a linked period of student-directed learning with staff available for consultation, a group discussion and a period of directed self-study based on the material covered in the session.

To prioritise the practical application of skills and concepts, the module is in part based around an outbreak scenario where students design an investigation and analysis plan, and students learn using hands-on practical learning. For the scenario, you will be given access to a large data set that mimics the inhabitants of a fictitious community in a tropical country and will be asked to design projects to address a series of research questions relating to tropical health issues in humans. You will then select an appropriate number of individuals from the data set and analyse the data using standard statistical computer packages such as EpiInfo, SPSS and/or R.

Through completion of the scenario students will learn and apply skills in:

1.  The design of health surveys, including the development of sampling frames, selection of (random / representative) samples, sample size calculations, stratification, as well as assessing for sources of sampling or measurement bias.
2. Design issues for the conduct of observational epidemiological studies, concentrating primarily on cohort, case-control and analytical survey study designs.
3. Designing an analysis plan to consider bias, collinearity and confounding. Statistical methods used to determine risk estimates and create explanatory and predictive models.

The module will also develop understanding of design issues and statistical analytical methods for the other health research designs, including the conduct of interventional randomised controlled trials (RCTs), spatial analysis and use of Geographical information Systems, meta-analysis for systematic reviews, and other common methods to analyse count data and survival data.

20 Academic Credits

100% – Written assignment. Students will be given a data set from an observational epidemiological study to analyse and write up as a formal report.

For an additional fee of £95, you can be entered for full Academic Credits for this course (Masters level credit). The academic credits are offered to provide choice and flexibility to all of our students and students who do not wish to do the assessments will be awarded a Certificate of Attendance.

Entrance Requirements

Academic requirements

Students with an academic background in statistics and epidemiology study design equivalent to that normally acquired a Research Module will be accepted on the module at the discretion of the Module Convenor. This would include a basic understanding of experimental and observational study design (clinical trials, surveys, case-control studies, cohort studies). It would also include a basic understanding of basic statistical concepts (types of data, summary statistics, principles of hypothesis testing, p values and confidence intervals, bias).

English language requirements

Attending course with Academic Credit:
The course is taught in English. Students whose first language is not English must provide evidence of their language skills. A full list is available on our website https://www.lstmed.ac.uk/english-language-requirements and https://www.lstmed.ac.uk/lstm-english-language-waiver-programme

Attending course – Certificate of Attendance Only:
The course is taught in English and in a postgraduate setting. Students whose first language is not English should be aware that to benefit from the course participants should have English language proficiency at the equivalent of an IELTS (International English Language Testing System) score of at least 6.5.