Power prior distributions for regression models

By Joseph G. Ibrahim, Ming-Hui Chen. 2000

817 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9ea02b9280defd812b466143b051909492d5a4ce

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Citations in the corpus

Robust meta‐analytic‐predictive priors in clinical trials with historical control information (2014, methodology): “The power prior (Ibrahim and Chen, 2000) has also been used to include prior information from one historical trial.”
A Simulation Study Comparison of Bayesian Estimation With Conventional Methods for Estimating Unknown Change Points (2008, background): “However, it has been shown that correctly specified informative priors can make the parameter estimates more accurate and effective ( Ibrahim & Chen, 2000 ; Zhang, Hamagami, Wang, Grimm, & Nesselroade, 2007 ).”
Estimating Cure Rates From Survival Data (2003, background): “Moreover, recent books discussing Gibbs sampling for this model and related models are also given in Ibrahim et al. (2001a) and Chen, Shao, and Ibrahim (2000).”
Model Averaging and Its Use in Economics (2017, methodology): “This idea of imaginary data is also related to the power prior approach (Ibrahim and Chen (2000) initially developed on the basis of the availability of historical data (i.e. data arising from previous similar studies).”
Conjugate priors for generalized linear models (2003, methodology): “Second, the power priors in Ibrahim and Chen (2000) assume the existence of historical data for the construction of the prior, take y0 to be the response vector corresponding to the raw historical data, and take the covariate matrix to be the covariate matrix corresponding to the historical data.”
A general framework for updating belief distributions (2013, background): “There are clear connections here with the use of ‘power priors’ (Ibrahim and Chen, 2000) where”
The Power Prior: Theory and Applications (2015, background): “Chen et al. [12] developed the power prior for variable selection and computation in the GLM, Chen et al. [31] extended these results to generalized linear mixed models, Ibrahim and Chen [1] and Ibrahim et al. [13] developed the variable selection methodology and computation for power priors in the ”