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

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 ...

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 ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

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 ...

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 ...

Extended educational sessions that offer attendees the opportunity to learn research methods and techniques from prominent psychological scientists.