Plot fixed or random effects coefficients for merMod objects.

Plot fixed or random effects coefficients for merMod objects.

# S3 method for merMod
plot_coefficients(
  model,
  order = "decreasing",
  sd_multi = 2,
  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.
sd_multi	For non-brmsfit objects, the multiplier that determines the width of the interval. Default is 2.
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.

Details

This plots the fixed or random effects of lme4 objects. For more information on the fixed effects, see plot_coefficients.It requires the lme4 package. The plot for random effects is basically the dotplot demonstrated at ?lme4::ranef, but instead uses ggplot2 so you would have a little easier time working with it to do with as you wish (for multiple random effects, a list of ggplot objects can be returned). Many of the options for fixed effects are removed, as they either don't make much sense or for practical reasons.

See also

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

Examples

library(lme4)
#> Loading required package: Matrix
fit_mer = lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
plot_coefficients(fit_mer, ranef = TRUE, which_ranef = 'Subject')
#> $`(Intercept)`
#> 
#> $Days
#>