€300 discount for FME-UPC students
€250 discount for students from other UPC or UB schools, adjunct faculty from UPC or UB, and full-time faculty from UB not affiliated with the MESIO program
€200 discount for students from other universities
Free for full-time faculty at the UPC and MESIO UB or involved departments
This course is part of the XVIII Summer School of the Master's degree in Statistics and Operations Research (MESIO UPC-UB).
The use of Bayesian methodologies to incorporate prior information has become a key tool in the design and analysis of clinical trials. This course offers a practical introduction to different information borrowing approaches, showing how existing knowledge or concurrent data can be leveraged to improve the accuracy of estimates and optimize the design of prospective studies. Both theoretical foundations and applied examples across different phases of clinical development will be covered.
The course on Bayesian Information Borrowing with Applications to the Design and Analysis of Clinical Trials is designed to provide familiarity with advanced techniques for integrating prior information into statistical models. Through a combination of theoretical lectures and practical case studies, participants will acquire useful tools to apply these methods in real-world contexts, contributing to more efficient, evidence-based decision-making.
Primarily intended for students of the MESIO master’s program. The seminars can be recognized with 3 ECTS if 2 courses are completed and passed, and with 5 ECTS if 3 courses are completed and passed, subject to approval by the Faculty of Mathematics.
Master students, applied statisticians in public and private sectors, trialists.
Participants should have completed a course on Likelihood and have basic knowledge of R.
Software Requirements
Students must bring their own laptops with R, RStudio, JAGS, rjags (R package) installed.