Plot the Power of a BSSR Design against the Fixed-Sample Design

Usage

# S3 method for class 'bbssr_powerbssr'
plot(
  x,
  main = NULL,
  sub = NULL,
  xlab = NULL,
  ylab = NULL,
  ylim = NULL,
  ref.line = NULL,
  legend.title = NULL,
  legend.labels = NULL,
  show.points = TRUE,
  colours = NULL,
  base_size = 11,
  ...
)

Arguments

x: An object of class bbssr_powerbssr returned by BinaryPowerBSSR
main: Title of the plot. The default of NULL builds the title from the object and a single NA drops it
sub: Subtitle of the plot, following the convention of main
xlab: Label of the horizontal axis, following the convention of main
ylab: Label of the vertical axis, following the convention of main
ylim: Numeric vector of length two giving the range of the vertical axis, or NULL for a range chosen from the data
ref.line: Numeric vector of heights at which a dashed horizontal line is drawn. The default of NULL places one line at the target power and a single NA draws no line
legend.title: Title of the legend. The default of NULL leaves the legend untitled
legend.labels: Character vector of length two replacing the entries of the legend, in the order BSSR then fixed sample
show.points: Logical. If TRUE, the default, a marker is drawn at every evaluated pooled probability. Set it to FALSE to draw the curves alone, which is easier to read on a fine grid
colours: Character vector of length two giving the colour of the two curves, in the order BSSR then fixed sample
base_size: Base font size of the theme, in points
...: Further arguments, currently ignored

Value

A ggplot object

Details

Setting Delta.T to 0 in BinaryPowerBSSR turns the two power columns into rejection probabilities under the null hypothesis. The default reference line at the target power is then out of place, and the level of significance passed through ref.line together with a rescaled ylim gives a readable plot of the type I error rate.

The vertical range is imposed with coord_cartesian, so points outside ylim are hidden rather than removed from the data.

Examples

# \donttest{
res <- BinaryPowerBSSR(
  p = seq(0.23, 0.47, by = 0.04),
  Delta.A = 0.3, Delta.T = 0.3,
  N1 = 39, N2 = 39, omega = 0.5, r = 1,
  alpha = 0.025, tar.power = 0.8, Test = 'Chisq'
)
plot(res)


# Type I error rate, with the reference line moved to the level of significance
tie <- BinaryPowerBSSR(
  p = seq(0.23, 0.47, by = 0.04),
  Delta.A = 0.3, Delta.T = 0,
  N1 = 39, N2 = 39, omega = 0.5, r = 1,
  alpha = 0.025, tar.power = 0.8, Test = 'Chisq'
)
plot(tie, ref.line = 0.025, ylim = c(0.015, 0.030), base_size = 14,
     show.points = FALSE,
     main = 'Type I error rate of the BSSR design', ylab = 'Type I error rate',
     legend.title = 'Design', legend.labels = c('BSSR', 'Fixed'))

# }