Bayesian Clinical Trial
Design Course
This course covers background material about Bayesian design and
analysis pertaining to randomized clinical trials, and a detailed
hypothetical paralle-group two-treatment sequential Bayesian design
along with a simulation for learn how the design performs. Bayesian
operating characteristics are emphasized, the most important of these
being the correctness of the decision regarding treatment effect.
Pre-course reading should take about 4 hours, and the in-class
portion will last 2 hours with significant time for questions and
discussion. The instructor is Frank
Harrell.
Learning Goals
- Become familiar with Bayes’ rule and Bayesian thinking
- Understand the importance of the direction of information flow in
conditional probabilities
- Learn many of the advantages of Bayesian clinical trial design and
interpretation
- Understand the full power of Bayesian thinking through a detailed
clinical trial example with explicit goals factored into Bayesian
stopping rules
Pre-course Study
- Introductory
Video: Frequentist vs. Bayes
Note: In addition to saying
that the Bayesian approach treats the treatment effect as random, it
also allows the true effect to be fixed, were only it possible to know
it. An uncertainty distribution for the effect can be thought of as a
device that captures how much we know about something we don’t know
exactly.
- Chapter 1 through
section 1.1.4 of Bayes Rules by AA Johnson, MQ Ott, M Dogucu
- Introduction to
Bayesian Statistics by Woody Lewenstein video
- Bayesian
analytical methods in cardiovascular clinical trials: Why, when, and
how by Samuel Heuts et al
- Using Bayesian
methods to augment the interpretation of critical care trials by FG
Zampieri et al, 2021
- A
Bayesian interpretation of a pediatric cardiac arrest trial
(THAPCA-OH) by MO Harhay et al
- Figures 1, 2, 3 in Dexamethasone
12 mg versus 6 mg for patients with COVID-19 and severe hypoxaemia: a
pre-planned, secondary Bayesian analysis of the COVID STEROID 2
trial by A Granholm et al
- Side-by-side
comparison of frequentist and Bayesian approaches and
properties
- Flowcharts
depicting frequentist and Basesian paradigms
- Football
multiplicities
In-Class Topics
Bayesian Analysis and
Design Resources