dev_ermod_bin_cov_sel: Perform covariate selection for linear ER model

In BayesERtools: Bayesian Exposure-Response Analysis Tools

Perform covariate selection for linear ER model

Description

This functions is used to develop an ER model with covariates for binary and continuous endpoints. projpred package is used for variable selection.

Usage

dev_ermod_bin_cov_sel(
  data,
  var_resp,
  var_exposure,
  var_cov_candidates,
  cv_method = c("LOO", "kfold"),
  k = 5,
  validate_search = FALSE,
  nterms_max = NULL,
  .reduce_obj_size = TRUE,
  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_cov_sel(
  data,
  var_resp,
  var_exposure,
  var_cov_candidates,
  cv_method = c("LOO", "kfold"),
  k = 5,
  validate_search = FALSE,
  nterms_max = NULL,
  .reduce_obj_size = TRUE,
  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_candidates	Candidate covariate names in character vector
cv_method	Cross-validation method. Default is "LOO" (recommended). Use "kfold" if you see warnings on Pareto k estimates.
k	Number of folds for kfold CV. Only used if cv_method is "kfold".
validate_search	Whether to validate the search. Default is FALSE. Recommend to set to TRUE for kfold CV. Do not use for LOO (run time would become too long).
nterms_max	Maximum number of terms to consider in the model. Default is NULL (all terms are considered).
.reduce_obj_size	Whether to reduce object size by removing some elements from projpred outputs that are not necessary for the functionality of this package.
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_cov_sel or ermod_lin_cov_sel.

Examples

data(d_sim_binom_cov_hgly2)

er_binary_cov_model <- dev_ermod_bin_cov_sel(
  data = d_sim_binom_cov_hgly2,
  var_resp = "AEFLAG",
  var_exposure = "AUCss_1000",
  var_cov_candidates = c(
    "BAGE_10", "BWT_10", "BGLUC",
    "BHBA1C_5", "RACE", "VISC"
  )
)

er_binary_cov_model




data(d_sim_lin)

ermod_lin_cov_sel <- dev_ermod_lin_cov_sel(
  data = d_sim_lin,
  var_resp = "response",
  var_exposure = "AUCss",
  var_cov_candidates = c("BAGE", "SEX")
)

ermod_lin_cov_sel

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