This draft guidance provides guidance to sponsors and applicants submitting investigational new drug applications (INDs), new ...

The U.S. Food and Drug Administration (FDA) has issued new draft guidance modernizing statistical methodologies used in ...

Bayesian methods in Structural Equation Modeling (SEM) represent a paradigm shift in statistical analysis, integrating prior beliefs with empirical data to derive robust parameter estimates. This ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

FDA proposes framework clinical trial designs to guide Bayesian methods, improving efficiency in drug development for rare and pediatric conditions.

US FDA issues guidance on modernizing statistical methods for clinical trials: Maryland Wednesday, January 14, 2026, 09:00 Hrs [IST] The US Food and Drug Administration today publ ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

Scientists have developed a method to identify symmetries in multi-dimensional data using Bayesian statistical techniques. Bayesian statistics has been in the spotlight in recent years due to ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...