dev_ermod_bin {BayesERtools} | R Documentation |
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 |
|
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
[Package BayesERtools version 0.2.3 Index]