BayesERtools (version 0.2.0)

dev_ermod_bin_exp_sel: 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,
  verbosity_level = 1,
  chains = 4,
  iter = 2000
)
dev_ermod_lin_exp_sel(
  data,
  var_resp,
  var_exp_candidates,
  verbosity_level = 1,
  chains = 4,
  iter = 2000
)

Value

An object of class ermod_bin_exp_sel.or ermod_lin_exp_sel

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

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.

Examples

# \donttest{
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