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 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).

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)