Special Issue on Novel Bayesian Methods in Biopharmaceutical Statistics

Guest Editors:

James D. Stamey, Baylor University, USA
Mani Lakshminarayanan, Independent consultant, USA

The deadline for submissions is November 1, 2022 but individual papers will be reviewed and published online on an ongoing basis.

This thematic special issue in OPEN STATISTICS is devoted to Bayesian methods applied to problems in pharmaceutical statistics.

Bayesian methods have taken a more prominent role in areas of pharmaceutical statistics in recent years. From the design of clinical trials and estimating probability of success to complicated Bayes models of “real world data”, Bayesian methods have become not only an important tool for pharmaceutical statisticians but also have been receiving recognition from health authorities. Papers describing either the development of new Bayesian methodology or novel applications of Bayes methods to pharmaceutical problems broadly construed are welcome.

Contributions to the Special Issue may address (but are not limited) to the following aspects:
• Clinical trials
• Non-clinical applications
• Adaptive designs
• Prior elicitation
• Use of historical studies
• Pre-clinical studies
• Real-world data and real-world evidence
• Decision theory
• Network Meta-Analysis
• Missing data
• Computational tools

All submissions to the Special Issue must be made electronically via the online submission system Editorial Manager:

https://www.editorialmanager.com/stat/default1.aspx

All manuscripts will undergo the standard peer-review process (single-blind, at least two independent reviewers). When entering your submission via the online submission system please choose the option “Special Issue on Novel Bayesian Methods in Biopharmaceutical Statistics”.

For more information, please visit our website
https://www.degruyter.com/journal/key/stat/html

Editorial Contact:

openstatistics@degruyter.com