ConditionalPower-class {adoptr}R Documentation

(Conditional) Power of a Design

Description

This score evaluates P[X2 > c2(design, X1) | X1 = x1]. Note that the distribution of X2 is the posterior predictive after observing X1 = x1.

Usage

ConditionalPower(dist, prior)

Power(dist, prior)

## S4 method for signature 'ConditionalPower,TwoStageDesign'
evaluate(s, design, x1,
  optimization = FALSE, ...)

Arguments

dist

a univariate distribution object

prior

a Prior object

s

Score object

design

object

x1

stage-one test statistic

optimization

logical, if TRUE uses a relaxation to real parameters of the underlying design; used for smooth optimization.

...

further optional arguments

See Also

Scores

Examples

prior <- PointMassPrior(.4, 1)
cp <- ConditionalPower(Normal(), prior)
evaluate(
   cp,
   TwoStageDesign(50, .0, 2.0, 50, 2.0, order = 5L),
   x1 = 1
)
# these two are equivalent:
expected(cp, Normal(), prior)
Power(Normal(), prior)


[Package adoptr version 0.2.2 Index]