The power prior: theory and applications.
The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A-to-Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Frequentist properties of power priors in posterior inference are established, and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials.
Department of Biostatistics, University of North Carolina, Chapel Hill, 27599, NC, U.S.A.
Joseph G
JG
Ibrahim
Department of Statistics, University of Connecticut, Storrs, CT, 06269, U.S.A.
Ming-Hui
MH
Chen
Department of Statistics, University of Connecticut, Storrs, CT, 06269, U.S.A.
Yeongjin
Y
Gwon
SAS Institute Inc., Cary, NC, U.S.A.
Fang
F
Chen
D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D065386:Historically Controlled Study; D016014:Linear Models; D015233:Models, Statistical; D012107:Research Design; D013223:Statistics as Topic / Q000379:methods
Bayesian design; borrowing; clinical trials; discounting; historical data; informative prior