Bradley P. Carlin

Affiliations: 
University of Minnesota, Twin Cities, Minneapolis, MN 
Area:
Public Health, Biostatistics Biology
Google:
"Bradley Carlin"
Cross-listing: PHTree

Children

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Fujun Wang grad student 2002 UMN
Murali Haran grad student 2003 UMN
Margaret B. Short grad student 2003 UMN
Xiaoping Jin grad student 2005 UMN
Freda W. Cooner grad student 2006 UMN
Haijun Ma grad student 2006 UMN
Brian P. Hobbs grad student 2010 UMN
Laura A. Hatfield grad student 2011 UMN
Ran Li grad student 2011 UMN
Wei Zhong grad student 2012 UMN
Hwanhee Hong grad student 2013 UMN
Harrison S. Quick grad student 2013 UMN
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Publications

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Lewis CJ, Sarkar S, Zhu J, et al. (2019) Borrowing from Historical Control Data in Cancer Drug Development: A Cautionary Tale and Practical Guidelines. Statistics in Biopharmaceutical Research. 11: 67-78
Zhao H, Hodges JS, Carlin BP. (2017) Diagnostics for generalized linear hierarchical models in network meta-analysis. Research Synthesis Methods
Zhao H, Hobbs BP, Ma H, et al. (2016) Combining Non-randomized and Randomized Data in Clinical Trials Using Commensurate Priors. Health Services & Outcomes Research Methodology. 16: 154-171
Schnell PM, Tang Q, Offen WW, et al. (2016) A Bayesian credible subgroups approach to identifying patient subgroups with positive treatment effects. Biometrics
Murray TA, Hobbs BP, Sargent DJ, et al. (2016) Flexible Bayesian survival modeling with semiparametric time-dependent and shape-restricted covariate effects. Bayesian Analysis. 11: 381-402
Zhao H, Hodges JS, Ma H, et al. (2016) Hierarchical Bayesian approaches for detecting inconsistency in network meta-analysis. Statistics in Medicine
Quick H, Carlin BP, Banerjee S. (2015) Heteroscedastic CAR models for areally referenced temporal processes for analyzing California asthma hospitalization data. Journal of the Royal Statistical Society. Series C, Applied Statistics. 64: 799-813
Murray TA, Hobbs BP, Carlin BP. (2015) COMBINING NONEXCHANGEABLE FUNCTIONAL OR SURVIVAL DATA SOURCES IN ONCOLOGY USING GENERALIZED MIXTURE COMMENSURATE PRIORS. The Annals of Applied Statistics. 9: 1549-1570
Hong H, Chu H, Zhang J, et al. (2015) A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons. Research Synthesis Methods
Hong H, Chu H, Zhang J, et al. (2015) Rejoinder to the discussion of "a Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons," by S. Dias and A. E. Ades. Research Synthesis Methods
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