dev_ermod_bin_exp_sel {BayesERtools} | R Documentation |
Exposure metrics selection for linear ER models
Description
This functions is used to develop an linear ER model with binary and continuous endpoint, using various exposure metrics and selecting the best one.
Usage
dev_ermod_bin_exp_sel(
data,
var_resp,
var_exp_candidates,
prior = rstanarm::default_prior_coef(stats::binomial()),
prior_intercept = rstanarm::default_prior_intercept(stats::binomial()),
verbosity_level = 1,
chains = 4,
iter = 2000
)
dev_ermod_lin_exp_sel(
data,
var_resp,
var_exp_candidates,
prior = rstanarm::default_prior_coef(stats::binomial()),
prior_intercept = rstanarm::default_prior_intercept(stats::binomial()),
prior_aux = rstanarm::exponential(autoscale = TRUE),
verbosity_level = 1,
chains = 4,
iter = 2000
)
Arguments
data |
Input data for E-R analysis |
var_resp |
Response variable name in character |
var_exp_candidates |
Candidate exposure variable names in character vector |
prior , prior_intercept , prior_aux |
|
verbosity_level |
Verbosity level. 0: No output, 1: Display steps, 2: Display progress in each step, 3: Display MCMC sampling. |
chains |
Number of chains for Stan. |
iter |
Number of iterations for Stan. |
Value
An object of class ermod_bin_exp_sel
.or ermod_lin_exp_sel
Examples
data(d_sim_binom_cov_hgly2)
ermod_bin_exp_sel <-
dev_ermod_bin_exp_sel(
data = d_sim_binom_cov_hgly2,
var_resp = "AEFLAG",
var_exp_candidates = c("AUCss_1000", "Cmaxss", "Cminss")
)
ermod_bin_exp_sel
data(d_sim_lin)
ermod_lin_exp_sel <- dev_ermod_lin_exp_sel(
data = d_sim_lin,
var_resp = "response",
var_exp_candidates = c("AUCss", "Cmaxss")
)
ermod_lin_exp_sel
[Package BayesERtools version 0.2.3 Index]