The FDA has released draft guidance on how sponsors can use Bayesian models for clinical trials.

Bayesian prediction and modeling have emerged as transformative tools in the design and management of clinical trials. By integrating prior knowledge with accumulating trial data, Bayesian methods ...

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

In this video interview, David Morton, PhD, director of biostatistics at Certara, outlines how increasing FDA support is helping drive adoption of Bayesian methods, particularly in rare disease 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, ...

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 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 ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...