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BACprior (version 2.1.1)

BACprior-package: Choice of the Hyperparameter Omega in the Bayesian Adjustment for Confounding (BAC) Algorithm

Description

The BACprior package contains functions to help the user select the omega value appearing in the BAC prior distribution of the covariate inclusion indicators of the outcome and exposure models.

Arguments

Author

Denis Talbot, Genevieve Lefebvre, Juli Atherton.

Maintainer: Denis Talbot denis.talbot@fmed.ulaval.ca

Details

Package:BACprior
Type:Package
Version:2.1.1
Date:2023-10-10
License:GPL (>=2)

References

Brookhart, M.A., van der Lan, M.J. (2006). A semiparametric model selection criterion with applications to the marginal structural model, Computational Statistics & Data Analysis, 50, 475-498.

Hoeting, J.A., Madigan D., Raftery, A.E., Volinsky C.T. (1999). Bayesian model averaging : A tutorial, Statistical Science, 16, 382-417.

Lefebvre, G., Atherton, J., Talbot, D. (2014). The effect of the prior distribution in the Bayesian Adjustment for Confounding algorithm, Computational Statistics & Data Analysis, 70, 227-240.

Wang, C., Parmigiani, G., Dominici, F. (2012). Bayesian effect estimation accounting for adjustment uncertainty, Biometrics, 68 (3), 661-671.