Title: Performs Bayesian Variable Selection on the Covariates in a
Description: Uses Stochastic Search Variable Selection to select important
covariates in the three hazard functions of a semi-competing risks model. This
function performs the Gibbs sampler for variable selection and a Metropolis-Hastings-Green sampler for the number of split points and parameters for the
three baseline hazard function. This function returns the posterior sample of
all quantities sampled in the Gibbs sampler after a burn-in period to a desired

Description: Contains four functions used in the DIC-tau_g procedure. SCRSELECT() and SCRSELECTRUN() uses Stochastic Search Variable Selection to select important
covariates in the three hazard functions of a semi-competing risks model. These functions perform the Gibbs sampler for variable selection and a Metropolis-Hastings-Green sampler for the number of split points and parameters for the
three baseline hazard function. The function SCRSELECT() returns the posterior sample of all quantities sampled in the Gibbs sampler after a burn-in period to a desired
file location, while the function SCRSELECTRUN() returns posterior values of important quantities to the DIC-Tau_g procedure in a list.
The function DICTAUG() returns a list containing the DIC values for the unique models visited by the DIC-Tau_g grid search.
The function ReturnModel() uses SCRSELECTRUN() and DICTAUG() to return a summary of the posterior coefficient vectors for the optimal model along with saving this posterior sample to a desired path location.

Description: A package for designing single-case phase, alternation and
multiple-baseline experiments, as well as for conducting
randomization tests on data gathered by means of such designs.

Description: A package for designing single-case phase, alternation and multiple-baseline experiments, as well as for conducting randomization tests on data gathered by means of such designs.

Description: Design single-case phase, alternation and multiple-baseline experiments, and conduct randomization tests on data gathered by means of such designs.