Flexible Evaluation of Surrogate Markers with Bayesian Model Averaging
Calculate prodiction MSE for nonparametric method
Function to be integrated when calculating the expected primary outcom...
Generates the default prior hyperparameters
Simple function using Rcpp
Calculates the posterior probability of the candidate models
Generates posterior samples of the parameters
Calculate the expected primary outcome in the treatment group given th...
Calculates the proportion of treatment effect explained
Calculates the proportion of treatment effect explained
Calculates the R value given model and parameters
Simple function using Rcpp
Flexible Evaluation of Surrogate Markers with Bayesian Model Averaging
Provides functions to estimate the proportion of treatment effect explained by the surrogate marker using a Bayesian Model Averaging approach. Duan and Parast (2023) <doi:10.1002/sim.9986>.