The US FDA has issued draft guidance supporting the use of Bayesian statistical models in drug and biologic trials, enabling sponsors to integrate prior and real-world data into study designs. This ...
To address the limitations of binary pCR classification, Pusztai and colleagues developed the residual cancer burden (RCB) ...
a.s.ist today announced the launch of a 7-day free trial for AutoStatSpectra, its Bayesian-statistics-based spectral analysis ...
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 ...
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 ...
The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...
The Annals of Applied Statistics, Vol. 14, No. 1 (March 2020), pp. 241-256 (16 pages) ABOUZAHR, C., CLELAND, J., COULLARE, F., MACFARLANE, S. B., NOTZON, F. C., SETEL ...
This study models graduation rates at 4-year broad access institutions (BAIs). We examine the student body, structural-demographic, and financial characteristics that best predict 6-year graduation ...
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