| BACprior-package {BACprior} | R Documentation |
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.
Details
| Package: | BACprior |
| Type: | Package |
| Version: | 2.1.1 |
| Date: | 2023-10-10 |
| License: | GPL (>=2) |
Author(s)
Denis Talbot, Genevieve Lefebvre, Juli Atherton.
Maintainer: Denis Talbot denis.talbot@fmed.ulaval.ca
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.