Industry groups and drugmakers want the US Food and Drug Administration (FDA) to explicitly clarify that Bayesian statistical methods can be used for products beyond those intended for children and ...

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 ...

Bayesian quantile regression extends the classical quantile regression framework by embedding it within a probabilistic paradigm, allowing direct inference on conditional quantiles through ...

The FDA’s new draft guidance on Bayesian methods in clinical trials has been hailed by some as a breakthrough that could speed drug development. But statisticians and researchers are divided on ...

The FDA's move to incorporate Bayesian statistical methods into clinical trials of drugs and biologics garnered special treatment in JAMA this week. JAMA published three perspectives -- two welcoming ...

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 ...

The "replication crisis" refers to a problem in the sciences where findings from previous experiments don't hold up when studies are repeated. It is a particular issue for those in the behavioral ...

Cobimetinib Plus Vemurafenib in Patients With Colorectal Cancer With BRAF Mutations: Results From the Targeted Agent and Profiling Utilization Registry (TAPUR) Study We divided the borrowing ...

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 ...

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