sim_er_new_exp_marg {BayesERtools} | R Documentation |
Calculate marginal expected response for specified exposure values
Description
Responses at specified exposure values are calculated for n_subj_sim
subjects with different covariates (sampled from newdata
),
and the predicted responses are "marginalized" (averaged),
resulting in marginal expected response on the
population of interest.
Usage
sim_er_new_exp_marg(
ermod,
exposure_to_sim_vec = NULL,
data_cov = extract_data(ermod),
n_subj_sim = 100,
n_draws_sim = 500,
seed_sample_draws = NULL,
output_type = c("draws", "median_qi"),
qi_width = 0.95
)
sim_er_curve_marg(
ermod,
exposure_range = NULL,
num_exposures = 51,
data_cov = extract_data(ermod),
n_subj_sim = 100,
n_draws_sim = 500,
seed_sample_draws = NULL,
output_type = c("draws", "median_qi"),
qi_width = 0.95
)
Arguments
ermod |
An object of class |
exposure_to_sim_vec |
Vector of exposure values to simulate. |
data_cov |
Data frame containing covariates to use for simulation.
Different from |
n_subj_sim |
Maximum number of subjects to simulate. Default of 100
should be sufficient in many cases, as it's only used for marginal
response calculation.
Set to NULL to use all subjects in |
n_draws_sim |
Number of draws for simulation. Default is set to 500 to reduce computation time for marginal response calculation. |
seed_sample_draws |
Seed for sampling draws. Default is NULL. |
output_type |
Type of output. "draws" returns the raw draws from the simulation, and "median_qi" returns the median and quantile interval. |
qi_width |
Width of the quantile interval. Default is 0.95. Only
used when |
exposure_range |
Range of exposure values to simulate. If NULL (default), it is set to the range of the exposure variable in the original data for model development. |
num_exposures |
Number of exposure values to simulate. |
Details
sim_er_new_exp_marg()
returns a tibble with the marginal expected
response for each exposure value in exposure_to_sim_vec
.
sim_er_curve_marg()
is a wrapper function for sim_er_new_exp_marg()
that use a range of exposure values to simulate the marginal expected
responses. Particularly useful for plotting the exposure-response curve.
Value
ersim_marg
object, which is a tibble with the simulated marginal
expected response with some additional information in object attributes.
In case of output_type = "median_qi"
, it returns ersim_marg_med_qi
object.
See Also
calc_ersim_med_qi()
for calculating median and quantile interval
from ersim_marg
object (generated with output_type = "draws"
).
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",
)
ersim_new_exp_marg_med_qi <- sim_er_new_exp_marg(
ermod_bin,
exposure_to_sim_vec = seq(2, 6, by = 0.2),
data_cov = dplyr::tibble(BHBA1C_5 = 4:10),
n_subj_sim = NULL,
n_draws_sim = 500, # This is set to make the example run faster
output_type = "median_qi"
)
ersim_new_exp_marg_med_qi