View source: R/autoplot.simsum.R
| autoplot.simsum | R Documentation | 
autoplot can produce a series of plot to summarise results of simulation studies. See vignette("C-plotting", package = "rsimsum") for further details.
## S3 method for class 'simsum'
autoplot(
  object,
  type = "forest",
  stats = "nsim",
  target = NULL,
  fitted = TRUE,
  scales = "fixed",
  top = TRUE,
  density.legend = TRUE,
  zoom = 1,
  zip_ci_colours = "yellow",
  ...
)
object | 
 An object of class   | 
type | 
 The type of the plot to be produced. Possible choices are:   | 
stats | 
 Summary statistic to plot, defaults to   | 
target | 
 Target of summary statistic, e.g. 0 for   | 
fitted | 
 Superimpose a fitted regression line, useful when   | 
scales | 
 Should scales be fixed (  | 
top | 
 Should the legend for a nested loop plot be on the top side of the plot? Defaults to   | 
density.legend | 
 Should the legend for density and hexbin plots be included? Defaults to   | 
zoom | 
 A numeric value between 0 and 1 signalling that a zip plot should zoom on the top x% of the plot (to ease interpretation). Defaults to 1, where the whole zip plot is displayed.  | 
zip_ci_colours | 
 A string with (1) a hex code to use for plotting coverage probability and its Monte Carlo confidence intervals (the default, with value   | 
... | 
 Not used.  | 
A ggplot object.
data("MIsim", package = "rsimsum")
s <- rsimsum::simsum(
  data = MIsim, estvarname = "b", true = 0.5, se = "se",
  methodvar = "method", x = TRUE
)
library(ggplot2)
autoplot(s)
autoplot(s, type = "lolly")
autoplot(s, type = "est_hex")
autoplot(s, type = "zip", zoom = 0.5)
# Nested loop plot:
data("nlp", package = "rsimsum")
s1 <- rsimsum::simsum(
  data = nlp, estvarname = "b", true = 0, se = "se",
  methodvar = "model", by = c("baseline", "ss", "esigma")
)
autoplot(s1, stats = "bias", type = "nlp")
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