BayesERtools (version 0.2.0)

plot_coveff: Visualize the covariate effects for ER model

Description

Visualize the covariate effects for ER model

Usage

plot_coveff(x, ...)
# S3 method for ermod
plot_coveff(
  x,
  data = NULL,
  spec_coveff = NULL,
  qi_width = 0.9,
  qi_width_cov = 0.9,
  ...
)
# S3 method for coveffsim
plot_coveff(x, ...)

Value

A ggplot object

Arguments

x

an object of class ermod, coveffsim, or their subclasses

...

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 sim_coveff() or plot_coveff(), if you have already built it manually or with build_spec_coveff(). See build_spec_coveff() for detail.

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).

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)