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 ...

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, ...

Many current statistical methods for disease clustering studies are based on a hypothesis testing paradigm. These methods typically do not produce useful estimates of disease rates or cluster risks.

In this video interview, David Morton, PhD, director of biostatistics at Certara, explains how regulatory momentum is ...

In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...

Artificial intelligence can solve problems at remarkable speed, but it's the people developing the algorithms who are truly driving discovery. At The University of Texas at Arlington, data scientists ...

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 ...

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 ...