Graduate School of health and Medical Sciences

Login for PhD students at UCPH Login for others

Introduction to advanced Bayesian adaptive trials: design and analysis
Provider: Faculty of Health and Medical Sciences

Activity no.: 3349-26-00-01	There are 3 available seats
	Enrollment deadline: 05/05/2026

Date and time	03.06.2026, at: 08:30 - 04.06.2026, at: 15:00
Regular seats	15
Course fee	3,240.00 kr.
Lecturers	Anders Granholm
ECTS credits	1.30

Contact person	Susanne Kragskov Laupstad E-mail address: skl@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration SUND E-mail address: phdkursus@sund.ku.dk

Enrolment guidelines This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at NorDoc member faculties. All other participants must pay the course fee. Learning objectives The course will provide students with an introduction to advanced Bayesian adaptive trials, making students able to participate in the design and analysis of such trials. A student who has met the objectives of the course will be able to: • Explain the most important methodological considerations in advanced Bayesian adaptive trials using adaptive stopping, arm dropping, and response-adaptive randomisation • Evaluate and compare selected performance metrics applicable to advanced Bayesian adaptive trial designs using statistical simulation • Specify, conduct, and evaluate simple Bayesian regression analyses of clinical trial data • Calculate sample-average treatment effects using G-computation • Evaluate adaptation rules for adaptive stopping, arm dropping, and response-adaptive randomisation Content The course provides an introduction to advanced Bayesian adaptive trials using adaptive stopping, adaptive arm dropping, and response-adaptive randomisation. The first day will focus on trial design and cover: • An introduction to adaptive trials • An introduction to Bayesian statistical methods • Key methodological decisions for advanced adaptive trials • Specifying advanced Bayesian trial designs and evaluating their performance metrics using statistical simulation The second day will focus on analysis and cover: • Specification of Bayesian models including covariates and priors • Bayesian model fitting using Markov chain Monte Carlo and evaluation using appropriate model diagnostics • Calculation of average treatment effect and posterior probabilities using G-computation • Adaptive (interim) analysis and evaluation of stopping rules and updating of allocation profiles The course focuses mostly on the practical application of the introduced methods and less on the theory and maths behind. The methods covered are also relevant for adaptive platform trials, but platform trials are not specifically covered during the course. Participants The course is targeted towards participants working with or planning to work with the design or analysis of clinical trials. To be able to follow the course, participants are expected to: • Have basic knowledge on statistics/data science (e.g., you have previously attended the Basic Statistics for Health Researchers PhD-course or similar) • Basic knowledge of using R statistical software • Basic knowledge about clinical trials Participants are not expected to have any previous experience with advanced adaptive trial designs, Bayesian statistical methods, or advanced programming in R. If you are uncertain if this course is for you, you are more than welcome to reach out. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: - All graduate programmes - Public Health and Epidemiology - Biostatistics and Bioinformatics Language English or Danish Form Two-day course consisting of lectures and hands-on computer exercises in small groups using R. Participants must bring a laptop with R installed. Course director Anders Granholm, MD PhD assistant professor, Section of Biostatistics and Rigshospitalet, anders.granholm@sund.ku.dk Teachers Aksel Karl Georg Jensen, MSc PhD assistant professor, Section of Biostatistics Anders Granholm, MD PhD assistant professor, Section of Biostatistics and Rigshospitalet Dates 3 and 4 June 2026, both days 8.30-15.00 Course location CSS Expected frequency Once or twice yearly. Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec