Micro-credential Design and Analysis of Randomized Clinical Trials
In a rapidly changing (professional) context, lifelong learning has become a must. With microcredentials Ghent University offers a new type of course for a broad group of lifelong learners.
Microcredentials are short academic programmes that meet the high quality standards of Ghent University. Both in terms of content and practice, the development of a microcredential is primarily focused on the needs of professionals and lifelong learners. The focus of the programme is on a well-defined set of learning outcomes. They consist of a limited number of subjects to which credits are linked. For following a microcredential, your learning account will be used . If you successfully complete the programme, you will receive credit certificates for the individual subjects and a recognised certificate that offers clear added value for professionals and employers. Microcredentials are organised by the 'academies for lifelong learning' of Ghent University.
This course is aimed at biologists, bioinformaticians and statisticians interested in analysing single-cell RNA-seq datasets.
This course builds on the course on Principles of statistical data analysis, Analysis of continuous data and Categorical Data Analysis to teach knowledge and ideas to draw evidence from randomized studies with a focus on applications in medicine and public health. It will provide the student with an understanding of statistical principles, methodology and concepts involved in clinical research across the various phases. The student should acquire the skills to design a clinical trial, be aware and understand the limitations related to clinical trials, be aware of formal guidelines and be able to analyze the data according to appropriate statistical techniques.
- Clinical Trials
- Protocol document and the role of the statistician therein
- Types of experimental designs (parallel, cross-over, factorial)
- Endpoints and estimands
- Sample Size/Power calculations
- Treatment allocation
- Data analysis and prognostic factors
- Concepts and methodology for (data-dependent) stopping and early termination of trials
- (interim analysis, adaptive designs and data monitoring committees)
- Reporting of results, potential pitfalls and data quality
The basics of statistical concepts, techniques and inference, knowledge of linear regression and categorical data analysis are considered known.
- The student has knowledge of statistical methods (including designs) for the analysis of clinical trials.
- The student can:
- give well-argued advice on clinical trial designs.
- properly perform advanced clinical trial data analyses.
- can draw appropriate conclusions from statistical analyses related to the clinical trial taking into account possible study design related bias.
- can report the results to scientists from subject matter fields.
- can critically comment on published clinical research.
There is an end-of-term written open book examination.
Type of course
This is an on campus course.
Syllabus, overheads, exercises handout
- Fundamentals of clinical trials. Friedman L., Furberg C., DeMets D. Springer-Verlag, New York 1998 (3rd edition)
- Pharmaceutical Statistics: practical and clinical applications. Bolton S., Bon C. Informa Health Care, 2004.
- Statistical Issues in Drug Development. Senn S. Wiley, Hoboken and Chichester (1997).
- Clinical Trials: A methodologic Perspective. Piantadosi S. Wiley & Sons, New Jersey, 2005 (2nd edition).
M2-Design and Analysis of Randomized Clinical Trials
Design and Analysis of Randomized Clinical Trials
- October 25, November 8, 22 & 29, December 6, 13 and 20, 2023, from 8.30 am to 11.30 am