Nothing
## ----include = FALSE------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 7,
fig.height = 5
)
## ----setup----------------------------------------------------------
library(adoptr)
## ----define-design--------------------------------------------------
design <- TwoStageDesign(
n1 = 100,
c1f = .0,
c1e = 2.0,
n2_pivots = rep(150, 5),
c2_pivots = sapply(1 + adoptr:::GaussLegendreRule(5)$nodes, function(x) -x + 2)
)
plot(design)
## -------------------------------------------------------------------
uniform_prior <- ContinuousPrior(
function(x) numeric(length(x)) + 1/.2,
support = c(.3, .5)
)
cp <- ConditionalPower(Normal(), uniform_prior)
css <- ConditionalSampleSize()
x1 <- c(0, .5, 1)
evaluate(cp, design, x1)
evaluate(css, design, x1)
## -------------------------------------------------------------------
plot(design, "Conditional Power" = cp)
## -------------------------------------------------------------------
ep <- expected(cp, Normal(), uniform_prior)
evaluate(ep, design)
## -------------------------------------------------------------------
power1 <- expected(
ConditionalPower(Normal(), PointMassPrior(.4, 1.0)),
Normal(), PointMassPrior(.4, 1.0)
)
power2 <- Power(Normal(), PointMassPrior(.4, 1.0))
evaluate(power1, design)
evaluate(power2, design)
## -------------------------------------------------------------------
ess1 <- expected(ConditionalSampleSize(), Normal(), uniform_prior)
ess2 <- ExpectedSampleSize(Normal(), uniform_prior)
evaluate(ess1, design)
evaluate(ess2, design)
## -------------------------------------------------------------------
cp >= 0.7
## -------------------------------------------------------------------
cp >= ConditionalPower(Normal(), PointMassPrior(0, 1))
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