adoptr (version 1.1.1)

ConditionalPower-class: (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, label = "Pr[x2>=c2(x1)|x1]")
Power(dist, prior, label = "Pr[x2>=c2(x1)]")
# S4 method for ConditionalPower,TwoStageDesign
evaluate(s, design, x1, optimization = FALSE, ...)

Arguments

dist

a univariate distribution object

prior

a Prior object

label

object label (string)

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)