# Tests for BESTpower
context("BESTpower_Pro")
test_that("BESTpower with 2 groups gives same output", {
proData <- makeData(mu1=108, sd1=17, mu2=100, sd2=15, nPerGrp=20,
pcntOut=15, sdOutMult=2.0, rnd.seed=1,
showPlot=FALSE)
expect_that(class(proData), equals("list"))
expect_that(round(proData$y1, 5),
is_equivalent_to(c(94.91088, 109.80678, 91.06461, 135.7637, 112.48891, 91.34337, 115.39274, 120.00616, 117.01734, 100.81456, 134.22832, 113.59835, 95.00674, 65.70652, 127.115, 105.60376, 106.13228, 144.94097, 116.18516, 62.87387)))
expect_that(round(proData$y2, 5),
is_equivalent_to(c(118.12939, 115.72711, 103.30548, 67.0728, 112.8777, 101.01111, 99.26143, 76.17697, 93.6024, 109.33356, 125.8485, 100.192, 108.80216, 101.05191, 77.82177, 94.71111, 95.07459, 59.30063, 130.72614, 109.97323)))
proMCMCs <- BESTmcmc(proData$y1, proData$y2, numSavedSteps=9,
burnInSteps = 1, verbose=FALSE, rnd.seed=2, parallel=FALSE)
proMCMCp <- BESTmcmc(proData$y1, proData$y2, numSavedSteps=9,
burnInSteps = 1, verbose=FALSE, rnd.seed=2, parallel=TRUE)
expect_equivalent(proMCMCs, proMCMCp)
expect_that(round(colMeans(proMCMCs), 5),
is_equivalent_to(c(105.88920, 101.17133, 39.46793, 23.61237, 17.94958)))
pow2s <- BESTpower(proMCMCs, N1=10, N2=10,
ROPEm=c(-2,2) , ROPEsd=c(-2,2) , ROPEeff=c(-0.5,0.5) ,
maxHDIWm=25.0 , maxHDIWsd=10.0 , maxHDIWeff=1.0 ,
nRep=9, mcmcLength=1000, verbose=0, rnd.seed=3, parallel=FALSE)
pow2p <- BESTpower(proMCMCs, N1=10, N2=10,
ROPEm=c(-2,2) , ROPEsd=c(-2,2) , ROPEeff=c(-0.5,0.5) ,
maxHDIWm=25.0 , maxHDIWsd=10.0 , maxHDIWeff=1.0 ,
nRep=9, mcmcLength=1000, verbose=0, rnd.seed=3, parallel=TRUE)
expect_equivalent(pow2s, pow2p)
expect_equal(class(pow2s), c("matrix", "array"))
expect_equal(colnames(pow2s), c("mean", "CrIlo", "CrIhi"))
expect_that(rownames(pow2s),
equals(c(" mean: HDI > ROPE", " mean: HDI < ROPE",
" mean: HDI in ROPE", " mean: HDI width ok",
" sd: HDI > ROPE", " sd: HDI < ROPE",
" sd: HDI in ROPE", " sd: HDI width ok",
"effect: HDI > ROPE", "effect: HDI < ROPE",
"effect: HDI in ROPE", "effect: HDI width ok")))
expect_equivalent(round(colMeans(pow2s), 5), c(0.09091, 0.00000, 0.25887))
})
test_that("BESTpower with 1 group gives same output", {
proData <- makeData(mu1=108, sd1=17, nPerGrp=20,
pcntOut=15, sdOutMult=2.0, rnd.seed=4,
showPlot=FALSE)
expect_that(class(proData), equals("list"))
expect_that(names(proData), equals(c("y1", "y2")))
expect_that(round(proData$y1, 5),
is_equivalent_to(c(102.74455, 86.85525, 116.85798, 110.68087, 132.43809, 112.63332, 71.39483, 93.74775, 137.89858, 135.39402, 110.0661, 98.53734, 106.22488, 97.26376, 98.92728, 101.74571, 122.5897, 140.77532, 122.08091, 61.14377)))
expect_null(proData$y2)
proMCMC <- BESTmcmc(proData$y1, proData$y2, numSavedSteps=9,
burnInSteps = 1, verbose=FALSE, rnd.seed=2)
expect_equivalent(round(colMeans(proMCMC), 5), c(111.74948, 29.43007, 22.10254))
pow1 <- BESTpower(proMCMC, N1=10, N2=10,
ROPEm=c(-2,2) , ROPEsd=c(-2,2) , ROPEeff=c(-0.5,0.5) ,
maxHDIWm=25.0 , maxHDIWsd=10.0 , maxHDIWeff=1.0 ,
nRep=9, mcmcLength=1000, verbose=0, rnd.seed=3)
expect_that(class(pow1), equals(c("matrix", "array")))
expect_that(colnames(pow1),
equals(c("mean", "CrIlo", "CrIhi")))
expect_that(rownames(pow1),
equals(c(" mean: HDI > ROPE", " mean: HDI < ROPE",
" mean: HDI in ROPE", " mean: HDI width ok",
" sd: HDI > ROPE", " sd: HDI < ROPE",
" sd: HDI in ROPE", " sd: HDI width ok",
"effect: HDI > ROPE", "effect: HDI < ROPE",
"effect: HDI in ROPE", "effect: HDI width ok")))
expect_equivalent(round(colMeans(pow1), 5), c(0.31818, 0.19418, 0.47534))
})
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