build_spec_coveff {BayesERtools} | R Documentation |
Build specifications for covariate effect simulation/visualization
Description
Build specifications for covariate effect simulation/visualization
Usage
build_spec_coveff(
ermod,
data = NULL,
qi_width_cov = 0.9,
n_sigfig = 3,
use_seps = TRUE,
drop_trailing_dec_mark = TRUE
)
Arguments
ermod |
an object of class |
data |
an optional data frame to derive the covariate values for forest plots. If NULL (default), the data used to fit the model is used. |
qi_width_cov |
the width of the quantile interval for continuous covariates in the forest plot. Default is 0.9 (i.e. visualize effect of covariate effect at their 5th and 95th percentile values). |
n_sigfig |
Number of significant figures to form value_label of
continuous variables. See |
use_seps |
Whether to use separators for thousands in printing numbers.
See |
drop_trailing_dec_mark |
Whether to drop the trailing decimal mark
(".") in value_label of continuous variables. See |
Value
spec_coveff
(return object) is a data frame for the specification
of the covariate effects to be visualized. This is internally generated by
build_spec_coveff()
if you run sim_coveff()
or plot_coveff()
directly. Alternatively, you can develop your own or modify the one
generated by build_spec_coveff()
and supply it to sim_coveff()
or
plot_coveff()
. The data frame should have the following columns (but
it's probably easier to try build_spec_coveff()
and see the structure):
-
var_order
: The order of the covariate in the forest plot. The exposure variable is always the first one and the covariates are ordered by the order they are supplied in thevar_cov
argument of thedev_ermod_*
function. If you used a model fromdev_ermod_bin_cov_sel()
, then the order is determined by the variable selection process. -
var_name
: The name of the variable. -
var_label
: The label of the variable to be used for plot. This is the same asvar_name
by default. -
value_order
: The order of the value of the variable to be evaluated. -
value_annot
: The annotation of the value of the variable to be evaluated. This appears on the right hand side of the forest plot. -
value_label
: The label of the value of the variable to be evaluated. -
value_cont
: The value for continuous variables. -
value_cat
: The value for categorical variables. -
is_ref_value
: Whether the value is the reference value. -
show_ref_value
: Whether to show the reference value in the plot and table. This is TRUE by default for is_ref_value == TRUE, otherwise NA (and ignored). -
is_covariate
: Whether the variable is a covariate (TRUE) or exposure variable (FALSE).
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 = c("BHBA1C_5", "RACE"),
)
spec_coveff <- build_spec_coveff(ermod_bin)
plot_coveff(ermod_bin, spec_coveff = spec_coveff)