This will give a plot of power vs. MDES or sample size. It can be useful to see how quickly power changes as a function of these design parameters. Can be useful to diagnose relatively flat power curves, where power changes little as a function of MDES or sample size, and can also be useful to gauge where convergence went poorly.
plot_power_curve(
pwr,
plot.points = TRUE,
all = TRUE,
low = NULL,
high = NULL,
grid.size = 5,
tnum = 2000,
breaks = grid.size,
fit = NULL
)plot; a ggplot object of power across values.
pumpresult object or data.frame; result from calling pump_sample or pump_mdes (or data frame from, e.g., power_curve()).
logical; whether to plot individually tested points on curve.
logical; if TRUE, merge in the search path from the original search.
scalar; low range for curve.
scalar; high range for the curve.
scalar; number of points to calculate power for.
scalar; number of iterations to calculate power at each grid point.
scalar; the desired number of tick marks on the axes.
a four parameter bounded logistic curve (if NULL will fit one to passed points).