Purpose: Risk assessment is an essential component of genetic counseling and testing, and Bayesian analysis plays a central role in complex risk calculations. We previously developed generalizable ...

Bayesian uncertainty analysis represents a powerful statistical framework that integrates prior knowledge with observed measurement data to quantify uncertainty in a consistent probabilistic manner.

We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...

In the 20th-century statistics wars, Bayesians were underdogs. Now their methods may help speed treatments to market.

Functional safety engineers follow the ISA/IEC 61511 standard and perform calculations based on random hardware failures. These result in very low failure probabilities, which are then combined with ...

As rare disease trials face persistent feasibility challenges, Bayesian designs are gaining momentum by enabling more flexible, data-driven approaches that integrate prior knowledge, reduce sample ...

Multilevel analysis is a useful technique for analyzing longitudinal data. To describe a person's development across time, the quality of the estimates of the random coefficients, which relate time to ...

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American I’m not sure when I first heard of Bayes’ ...