Plot a power analysis curve

Draws statistical power against sample size, with a dashed line at a target power (80% by default). The input is usually a power curve produced by simr::powerCurve(), though a tidy data frame works equally well, allowing the plot to be redrawn without repeating a power simulation that is often slow to run.

Usage

power_curve_plot(
  x,
  target = 0.8,
  x_lab = "Sample size",
  x_breaks = NULL,
  x_expand = NULL,
  ribbon = TRUE,
  title = NULL,
  interaction = c("times", "asterisk", "colon", "space")
)

Arguments

x

A powerCurve object from 'simr', or a data frame with a sample size column (nlevels, n or x), a power column (mean or power), and optional lower/upper confidence limits.

target

Target power, drawn as a horizontal reference line. Use NA to omit it.

x_lab

X-axis label.

x_breaks

Approximate number of x-axis breaks.

x_expand

Optional value(s) to extend the x-axis to.

ribbon

Whether to draw the confidence band as a shaded ribbon (TRUE) or as error bars (FALSE).

title

Plot title. If NULL and x is a 'simr' power curve, the predictor name stored in the object is used.

interaction

Passed to format_terms() when deriving the title from a 'simr' object.

Value

A ggplot2::ggplot object.

Examples

pc <- data.frame(
  nlevels = c(10, 20, 30, 40, 50, 60),
  mean = c(0.18, 0.34, 0.52, 0.66, 0.79, 0.88),
  lower = c(0.10, 0.25, 0.42, 0.56, 0.70, 0.81),
  upper = c(0.28, 0.44, 0.62, 0.75, 0.86, 0.93)
)
power_curve_plot(pc, title = "Power for the condition effect")