sse (version 0.7-17)

plot: Power Plot

Description

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.

Usage

plot(x, y, ...)

Arguments

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.

Value

A plot is generated but nothing is returned.

Details

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).

See Also

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

Examples

# NOT RUN {
## 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)
# }