plot_coefficients.brmsfit: Plot fixed or random effects coefficients for brmsfit...

In m-clark/visibly: Functions and palettes related to visual enhancement

Description

Plot fixed or random effects coefficients for brmsfit objects.

Usage

## S3 method for class 'brmsfit'
plot_coefficients(
  model,
  order = "decreasing",
  prob = 0.95,
  keep_intercept = FALSE,
  palette = "bilbao",
  ref_line = 0,
  trans = NULL,
  plot = TRUE,
  ranef = FALSE,
  which_ranef = NULL,
  ...
)

Arguments

model	The model. For example, lm, glm, gam, lme4, brms.
order	The order of the plots- "increasing", "decreasing", or a numeric vector giving the order. The default is NULL, i.e. the default ordering. Not applied to random effects.
prob	For brmsfit objects, the interval for the uncertainty level. Default is .95.
keep_intercept	Default is FALSE. Intercepts are typically on a very different scale than covariate effects.
palette	A scico palette. Default is 'bilbao'.
ref_line	A reference line. Default is zero.
trans	A transformation function to be applied to the coefficients (e.g. exponentiation).
plot	Default is TRUE, but sometimes you just want the data.
ranef	If applicable, whether to plot random effects instead of fixed effects.
which_ranef	If plotting random effects, which one to plot.
...	Other arguments applied for specific methods.

Value

A ggplot of the coefficients and their interval estimates. Or the data that would be used to create the plot.

See Also

Other model visualization: plot_coefficients.lm(), plot_coefficients.merMod(), plot_coefficients(), plot_gam_2d(), plot_gam_3d(), plot_gam_check(), plot_gam()

Examples

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m-clark/visibly documentation built on Oct. 28, 2020, 5:33 p.m.