dreamer - Dose Response Models for Bayesian Model Averaging
Fits dose-response models utilizing a Bayesian model averaging approach as outlined in Gould (2019) <doi:10.1002/bimj.201700211> for both continuous and binary responses. Longitudinal dose-response modeling is also supported in a Bayesian model averaging framework as outlined in Payne, Ray, and Thomann (2024) <doi:10.1080/10543406.2023.2292214>. Functions for plotting and calculating various posterior quantities (e.g. posterior mean, quantiles, probability of minimum efficacious dose, etc.) are also implemented. Copyright Eli Lilly and Company (2019).
Last updated 1 months ago
bayesiandose-response-modelingjagscpp
5.26 score 9 stars 5 scripts 244 downloadsbeaver - Bayesian Model Averaging of Covariate Adjusted Negative-Binomial Dose-Response
Dose-response modeling for negative-binomial distributed data with a variety of dose-response models. Covariate adjustment and Bayesian model averaging is supported. Functions are provided to easily obtain inference on the dose-response relationship and plot the dose-response curve.
Last updated 9 months ago
jagscpp
3.89 score 1 stars 77 scripts 242 downloadsyodel - A General Bayesian Model Averaging Helper
Provides helper functions to perform Bayesian model averaging using Markov chain Monte Carlo samples from separate models. Calculates weights and obtains draws from the model-averaged posterior for quantities of interest specified by the user. Weight calculations can be done using marginal likelihoods or log-predictive likelihoods as in Ando, T., & Tsay, R. (2010) <doi:10.1016/j.ijforecast.2009.08.001>.
Last updated 10 months ago
3.18 score 1 dependents 164 downloads