Bayesian shrinkage estimation of credible subgroups for count data with excess zeros-Reference-Cited by-同舟云学术

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Bayesian shrinkage estimation of credible subgroups for count data with excess zeros

Published:2024-08-05 Issue: Volume: Page:1-24
ISSN:1946-6315
Container-title:Statistics in Biopharmaceutical Research
language:en
Short-container-title:Statistics in Biopharmaceutical Research

Author:

Ngo Duy¹,Quartey Daniel²,Schnell Patrick M³,Baumgartner Richard⁴,Mt-Isa Shahrul⁵,Feng Dai⁶

Affiliation:

1. Department of Statistics, Western Michigan University

2. Structural Heart & Aortic, Medtronic PLC.

3. Division of Biostatistics, The Ohio State University College of Public Health

4. BARDS (Biostatistics and Research Decision Sciences), Merck & Co., Inc.

5. BARDS (Biostatistics and Research Decision Sciences), MSD.

6. Medical Affairs and Health Technology Assessment Statistics, AbbVie Inc.

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/19466315.2024.2388520

Reference60 articles.

1. Albert A. and Anderson J. A. (1984) ‘On the existence of maximum likelihood estimates in logistic regression models’ Biometrika 71(1) 1–10.

2. Albert J. M. Wang W. and Nelson S. (2014) ‘Estimating overall exposure effects for zero-inflated regression models with application to dental caries’ Statistical methods in medical research 23(3) 257–278.

3. Baetschmann G. and Winkelmann R. (2013) ‘Modeling zero-inflated count data when exposure varies: With an application to tumor counts’ Biometrical Journal 55(5) 679–686.

4. Ballarini N. M. Rosenkranz G. K. Jaki T. König F. and Posch M. (2018) ‘Subgroup identification in clinical trials via the predicted individual treatment effect’ PloS one 13(10) e0205971.

5. Beckman R. A. Clark J. and Chen C. (2011) ‘Integrating predictive biomarkers and classifiers into oncology clinical development programmes’ Nature reviews Drug discovery 10(10) 735–748.

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