plot: Power Plot
In sse: Sample Size Estimation

Description Usage Arguments Details Value See Also Examples

A sensitivity plot (called power plot) for the sample size calculation. Using a contour for a given power, it shows how sample size changes if theta is varied.

1	plot(x, y, ...)

x

The object of class power used for plotting

y

Not used

...

additional arguments implemented:

at = c(0.9, 0.8, 0.85, 0.95) a numeric vector giving breakpoints along the power range. Contours (if any) will be drawn at these values. The contour line of the example will be emphasised. If example = FALSE the first number indicates, which contour should be emphasized.
smooth = FALSE logical that indicates if the contours should be smoothed. If TRUE a span of 0.75 will be used by default. Alternatively the argument smooth can also take a numeric value that will be used for smoothing.See the documentation of the function loess for details.
example = TRUE a logical indicating if an example should be drawn or not. An example is an arrow that points from the particular theta on the x-axis to the contour line and to the sample size on the y-axis.
reflines = TRUE a logical indicating if reference lines should be drawn or not. Reference lines are drawn at every n and theta that was used for evaluating the power function. If reference lines are drawn the background will be grey.

Generates a contour plot with theta on the x-axis and n on the y-axis and the contours for the estimated power (indicated with the argument at).

A plot is generated but nothing is returned.

inspect for drawing an inspection plot and levelplot for further arguments that can be passed to plot.

## defining the range of n and theta to be evaluated
psi <- powPar(theta = seq(from = 0.5, to = 1.5, by = 0.1),
              n = seq(from = 20, to = 60, by = 2),
              muA = 0,
              muB = 1)

## defining a power-function     
powFun <- function(psi){
  power.t.test(n = n(psi)/2,
               delta = pp(psi, "muA") - pp(psi, "muB"),
               sd = theta(psi)
               )$power
}

## evaluating the power-function for all combinations of n and theta
calc <- powCalc(psi, powFun)

## adding example at theta of 1 and power of 0.9
pow <- powEx(calc, theta = 1, power = 0.9)

## drawing the power plot with 3 contour lines
plot(pow,
     xlab = "Standard Deviation",
     ylab = "Total Sample Size",
     at = c(0.85, 0.9, 0.95))

## without example the contour line at the first element of at is bold
plot(pow, example = FALSE)