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Fitted versus observed plot for brmsfit Objects

Source: R/ppc_brms.R
ppc_brms.Rd

Plot fitted versus observed values, including confidence interval (gray area) around best fit line (linear regression line) and prediction interval (dashed line).

Usage

ppc_brms(
  object,
  xtitle = "Observed value",
  ytitle = "Fitted value",
  dy = c(0.1, 0.1),
  dx = c(0.1, 0.1),
  cor = FALSE,
  equation = FALSE,
  xcor = NULL,
  ycor = NULL,
  xequ = NULL,
  yequ = NULL,
  ...
)

Arguments

object

An object of class brmsfit

xtitle

The text for the x-axis title

ytitle

The text for the y-axis title

dy

Distance from plot to y-axis

dx

Distance from plot to x-axis

cor

If TRUE, add correlation coefficients with p-values and R

equation

If TRUE, add regression line equation

xcor, ycor

numeric Coordinates (in data units) to be used for absolute positioning of the correlation coefficients

xequ, yequ

numeric Coordinates (in data units) to be used for absolute positioning of the regression line equation

...

Passed to lehuynh_theme()

Value

A ggplot object

Examples

if (FALSE) {

library(brms)

mod <- brm(count ~ zAge + zBase * Trt + (1|patient) + (1|obs),
           data = epilepsy,
           family = poisson())

ppc_brms(mod)
ppc_brms(mod, dy = c(0.02, 0.1), dx = c(0.005, 0.1))
ppc_brms(mod, cor = TRUE, equation = TRUE, yequ = 100)
}