CEBU offers a core sequence of research methods courses (redesigned in 2020). It is strongly recommended that the first three courses below be taken in sequence, because the later ones assume familiarity with concepts, language and techniques introduced earlier. The sequence begins with Foundations of Health Research Methods, which places a strong emphasis on clarifying the research question (with the understanding that most questions have a fundamentally causal nature), followed by Introduction to Biostatistics, which covers the key underlying concepts and most commonly used methods of statistics, and concluding with Observational Studies: Modern Concepts and Analytic Methods, which focuses on the challenges of causal inference in observational (non-randomised) studies with an introduction to regression methods. The last two courses in the list have a more specific practical focus on essential concepts and tools for sound and reliable data management.
An introduction to the key aspects of clinical research such as understanding the types of research questions we may ask, specifying and refining a research question and corresponding research design, drafting an analysis plan, understanding the regulatory environment we operate in and more.
A comprehensive introduction to the most commonly used methods of statistical analysis in clinical research, with a focus on simple study designs such as randomised trials and emphasis on the key underlying concepts of statistics and the interpretation of statistical findings.
Observational studies: Modern concepts & analytic methods (formerly Intro to Causal Inference and Regression)
A comprehensive introduction to key causal inference concepts, which are especially important with observational (non-randomised) studies, with an introduction to using regression methods for causal inference purposes and an emphasis on analysis planning to strengthen the quality of causal inferences we make from data.
This course takes a look at many aspects of managing research project data throughout the life of a project, from designing a database for capturing good quality data, through to cleaning data and preparing it for analysis.
The course is delivered as a classroom session. It is strongly recommened that you also enrol in the My Data Rules hands-on session on the following morning.
You have collected your research data. How do you make it ready to use in your analysis?
This half day course is a hands-on session in a computer lab. Participants will work through a recipe for converting raw data into clean datasets that can support robust, reliable and reproducible research results.