This study aimed to assess mixture effects of 16 targeted PAHs on male reproductive health by applying a novel grouping approach to the Bayesian kernel machine regression (BKMR) model. Bay region and molecular
Description Bayesian kernel machine regression(from the'bkmr'package)is a Bayesian semi-parametric generalized linear model approach under identity and probit links.There are a number of functions in this package that extend Bayesian kernel machine regressionfits to allow multiple-chain inference and ...
The R package bkmr implements Bayesian kernel machine regression, a statistical approach for estimating the joint health effects of multiple concurrent exposures. Additional information on the statistical methodology and on the computational details are provided in Bobb et al. 2015. More recent extensions...
Approach 2 – Bayesian Kernel Machine Regression (BKMR) BKMR was proposed as a new approach to assess the effect of exposure to chemical mixtures on health [34]. An R package (‘bkmr’) exists for this purpose, with the possibility of adapting the model to binary outcomes, like breast canc...
A novel statistical method, Bayesian kernel machine regression (BKMR), has been developed to examine the effects of mixtures on health outcomes (Bobb et al., 2015; Wei et al., 2020; Yin et al., 2020a). This model is capable of estimating the overall exposure-response function of the ...
We assessed the variable selection ability of: (1) Bayesian Kernel Machine Regression (BKMR), (2) Bayesian Semiparametric Regression (BSR), and (3) Bayesian Least Absolute Shrinkage and Selection Operator (BLASSO) regression on simulated data of different dimensions and under three scenarios with ...
Our findings demonstrate that BKMR outperforms the Poisson regression model, offering greater flexibility and robustness. Moreover, it provides the ability to quantify uncertainty in model parameters, enhancing the capacity to make inferences about the real world. This research has substantial implications...
Bayesian kernel machine regression. Contribute to jenfb/bkmr development by creating an account on GitHub.
The combined effects of Cd, As, and Hg on renal tubular damage markers were assessed using linear regression and a Bayesian Kernel Machine Regression (BKMR) model. The results of the BKMR model were compared using a stratified analysis of the exposure and control groups. While the linear ...