plot_coveff {BayesERtools} | R Documentation |
Visualize the covariate effects for ER model
Description
Visualize the covariate effects for ER model
Usage
plot_coveff(x, ...)
## S3 method for class 'ermod'
plot_coveff(
x,
data = NULL,
spec_coveff = NULL,
qi_width = 0.9,
qi_width_cov = 0.9,
...
)
## S3 method for class 'coveffsim'
plot_coveff(x, ...)
Arguments
x |
an object of class |
... |
currently not used |
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. |
spec_coveff |
you can supply spec_coveff to |
qi_width |
the width of the credible interval on the covariate effect. This translate to the width of the error bars in the forest plot. |
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). |
Value
A ggplot object
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",
)
plot_coveff(ermod_bin)
[Package BayesERtools version 0.2.3 Index]