A Bayesian Approach to Subgroup Identification
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2014/01/02
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Indian UGC (journal)
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Refrences26
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Citations75
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James O. Berger a Department of Statistical Science , Duke University , Durham , North Carolina , USA
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Xiaojing Wang b Department of Statistics , University of Connecticut , Storrs , Connecticut , USA
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Lei Shen c Eli Lilly and Company , Lilly Corporate Center , Indianapolis , Indiana , USA
Cite
Berger, James O., et al. “A Bayesian Approach to Subgroup Identification”. Journal of Biopharmaceutical Statistics, vol. 24, no. 1, 2014, pp. 110-29, https://doi.org/10.1080/10543406.2013.856026.
Berger, J. O., Wang, X., & Shen, L. (2014). A Bayesian Approach to Subgroup Identification. Journal of Biopharmaceutical Statistics, 24(1), 110-129. https://doi.org/10.1080/10543406.2013.856026
Berger, James O., Xiaojing Wang, and Lei Shen. “A Bayesian Approach to Subgroup Identification”. Journal of Biopharmaceutical Statistics 24, no. 1 (2014): 110-29. https://doi.org/10.1080/10543406.2013.856026.
Berger JO, Wang X, Shen L. A Bayesian Approach to Subgroup Identification. Journal of Biopharmaceutical Statistics. 2014;24(1):110-29.
Journal Categories
Medicine
Public aspects of medicine
Toxicology
Poisons
Medicine
Therapeutics
Pharmacology
Science
Mathematics
Probabilities
Mathematical statistics
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Subgroup identification based on differential effect search—A recursive partitioning method for establishing response to treatment in patient subpopulations | Statistics in Medicine |
| 174 | 2011 |
| Subgroup identification based on differential effect search—A recursive partitioning method for establishing response to treatment in patient subpopulations | Journal of Machine Learning Research |
| 2009 | |
| Subgroup identification based on differential effect search—A recursive partitioning method for establishing response to treatment in patient subpopulations | Biometrics |
| 1990 | |
| The Prospects for “Personalized Medicine” in Drug Development and Drug Therapy | Clinical Pharmacology & Therapeutics |
| 106 | 2007 |
| A Bayesian perspective on the Bonferroni adjustment | Biometrika |
| 172 | 1997 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024 | Journal of Clinical Lipidology |
| 2024 | |
| Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024 | Obesity Pillars | 2024 | ||
| Heterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition | Journal of the American Statistical Association |
| 2024 | |
| Bayesian optimal designs for multi-arm multi-stage phase II randomized clinical trials with multiple endpoints | Statistics in Biopharmaceutical Research |
| 2024 | |
Subgroup analysis for longitudinal data based on a partial linear varying coefficient model with a change plane | Statistics in Medicine |
| 2023 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 51
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Subgroup identification for treatment selection in biomarker adaptive design and was published in 2015. The most recent citation comes from a 2024 study titled Obesity, dyslipidemia, and cardiovascular disease: A joint expert review from the Obesity Medicine Association and the National Lipid Association 2024. This article reached its peak citation in 2017, with 17 citations. It has been cited in 33 different journals, 15% of which are open access. Among related journals, the Statistics in Medicine cited this research the most, with 10 citations. The chart below illustrates the annual citation trends for this article.