dev_ermod_emax {BayesERtools}R Documentation

Develop Emax model for continuous and binary endpoint

Description

These functions are used to develop an Emax model with continuous or binary endpoint. You can also specify covariates to be included in the model; note that only categorical covariates are allowed.

Usage

dev_ermod_emax(
  data,
  var_resp,
  var_exposure,
  l_var_cov = NULL,
  gamma_fix = 1,
  e0_fix = NULL,
  emax_fix = NULL,
  priors = NULL,
  verbosity_level = 1,
  chains = 4,
  iter = 2000,
  seed = sample.int(.Machine$integer.max, 1)
)

dev_ermod_bin_emax(
  data,
  var_resp,
  var_exposure,
  l_var_cov = NULL,
  gamma_fix = 1,
  e0_fix = NULL,
  emax_fix = NULL,
  priors = NULL,
  verbosity_level = 1,
  chains = 4,
  iter = 2000,
  seed = sample.int(.Machine$integer.max, 1)
)

Arguments

data

Input data for E-R analysis

var_resp

Response variable name in character

var_exposure

Exposure variable names in character

l_var_cov

a names list of categorical covariate variables in character vector. See details in the param.cov argument of rstanemax::stan_emax() or rstanemax::stan_emax_binary()

gamma_fix

Hill coefficient, default fixed to 1. See details in rstanemax::stan_emax() or rstanemax::stan_emax_binary()

e0_fix

See details in rstanemax::stan_emax() or rstanemax::stan_emax_binary()

emax_fix

See details in rstanemax::stan_emax() or rstanemax::stan_emax_binary()

priors

See details in rstanemax::stan_emax() or rstanemax::stan_emax_binary()

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.

seed

Random seed for Stan model execution, see details in rstan::sampling() which is used in rstanemax::stan_emax() or rstanemax::stan_emax_binary()

Value

An object of class ermod_emax.or ermod_bin_emax.

Examples



data_er_cont <- rstanemax::exposure.response.sample

ermod_emax <-
  dev_ermod_emax(
    data = data_er_cont,
    var_exposure = "exposure",
    var_resp = "response"
  )

plot_er(ermod_emax, show_orig_data = TRUE)

data_er_cont_cov <- rstanemax::exposure.response.sample.with.cov

ermod_emax_w_cov <-
  dev_ermod_emax(
    data = data_er_cont_cov,
    var_exposure = "conc",
    var_resp = "resp",
    l_var_cov = list(emax = "cov2", ec50 = "cov3", e0 = "cov1")
  )




data_er_bin <- rstanemax::exposure.response.sample.binary

ermod_bin_emax <-
  dev_ermod_bin_emax(
    data = data_er_bin,
    var_exposure = "conc",
    var_resp = "y"
  )

plot_er(ermod_bin_emax, show_orig_data = TRUE)

ermod_bin_emax_w_cov <-
  dev_ermod_bin_emax(
    data = data_er_bin,
    var_exposure = "conc",
    var_resp = "y_cov",
    l_var_cov = list(emax = "sex")
  )



[Package BayesERtools version 0.2.3 Index]