dev_ermod_bin: Develop linear ER model for binary or continuous endpoint

In BayesERtools: Bayesian Exposure-Response Analysis Tools

Develop linear ER model for binary or continuous endpoint

Description

These functions are used to develop an linear ER model with binary (dev_ermod_bin()) or continuous (dev_ermod_lin()) endpoint. You can also specify covariates to be included in the model.

Usage

dev_ermod_bin(
  data,
  var_resp,
  var_exposure,
  var_cov = NULL,
  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(
  data,
  var_resp,
  var_exposure,
  var_cov = NULL,
  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_exposure	Exposure variable names in character
var_cov	Covariate variable names in character vector
prior, prior_intercept, prior_aux	See rstanarm::stan_glm()
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 or ermod_lin.

Examples

data(d_sim_binom_cov_hgly2)

ermod_bin <- dev_ermod_bin(
  data = d_sim_binom_cov_hgly2,
  var_resp = "AEFLAG",
  var_exposure = "AUCss_1000",
  var_cov = "BHBA1C_5",
)

ermod_bin



data(d_sim_lin)

ermod_lin <- dev_ermod_lin(
  data = d_sim_lin,
  var_resp = "response",
  var_exposure = "AUCss",
  var_cov = c("SEX", "BAGE")
)

ermod_lin

BayesERtools documentation built on June 8, 2025, 1:26 p.m.