Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

In a new draft guidance issued on January 14, 2026, the FDA discussed the use of a modern statistical methodology in clinical trials designed to ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

BioStem remains committed to advancing evidence-based innovation in wound care through rigorous clinical research and real-world data analysis, supported by its proprietary BioRetain ® process and ...

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, ...

The US Food and Drug Administration (FDA) is now “open to bayesian statistics,” contrasting this with the frequentist approach that the agency and the drug industry have historically relied on for ...

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 ...

Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with effectively modeled probabilities.

Members of the university community are invited to participate in a workshop on "Modern Methods for Data Analysis" from Monday, Jan. 11 through Friday, Jan. 15, from 10 a.m. to noon (EST). The ...