Nothing
tests/testthat/test-anova_exact.R
In Superpower: Simulation-Based Power Analysis for Factorial Designs
context("test-anova_exact")
# error messages
test_that("error messages", {
design <- ANOVA_design(design = "2b*4w",
n = 7,
mu = c(0,0,0,0,0.5,0.5,0.5,0.5),
sd = 1,
plot = FALSE)
expect_error(ANOVA_exact(), "argument \"design_result\" is missing, with no default")
expect_error(ANOVA_exact(design, verbose = FALSE),
fixed = TRUE)
expect_error(ANOVA_exact2())
design <- ANOVA_design(design = "2b*4w",
n = 75,
mu = c(0,0,0,0,0.5,0.5,0.5,0.5),
sd = 1,
plot = FALSE)
expect_error(ANOVA_exact2(design,
emm = TRUE,
emm_model = "NOT"))
expect_error(ANOVA_exact2(design,
emm = TRUE,
contrast_type = "NOT"))
expect_error(ANOVA_exact2(design,
emm = TRUE,
correction = "none1"))
expect_error(ANOVA_exact2(design,
emm = TRUE,
alpha_level = 1.05))
expect_error(ANOVA_exact(design,
emm = TRUE,
emm_model = "NOT"))
expect_error(ANOVA_exact(design,
emm = TRUE,
contrast_type = "NOT"))
expect_error(ANOVA_exact(design,
emm = TRUE,
correction = "none1"))
expect_error(ANOVA_exact(design,
emm = TRUE,
alpha_level = 1.05))
})
#2w null
test_that("2w null", {
design <- ANOVA_design(design = "2w", n = 100,
mu = c(0, 0),
sd = 1,
r = 0.5,
plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 = ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 5)
expect_equal(p$pc_results$power, 5)
expect_equal(p2$main_results, p$main_results)
# confint error
expect_error(confint(p))
})
#2b null
test_that("2b null", {
design <- ANOVA_design(design = "2b", n = 100, mu = c(0, 0), sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 = ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 5)
expect_equal(p$main_results$power, p2$main_results$power)
expect_equal(p$pc_results$power, 5)
})
#2w moderate effect
test_that("2w", {
design <- ANOVA_design(design = "2w", n = 21, mu = c(0, 0.65), sd = 1, r = 0.55, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 84.7, tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.1)
expect_equal(p$pc_results$power, 84.7, tolerance = 0.1)
})
#2b moderate effect
test_that("2b", {
design <- ANOVA_design(design = "2b", n = 22, mu = c(0, 0.65), sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 55.8, tolerance = 0.05)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$pc_results$power, 55.8, tolerance = 0.1)
})
#3w null
test_that("3w null", {
design <- ANOVA_design(design = "3w", n = 100,
mu = c(0, 0, 0), sd = 1, r = 0.5, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 5)
expect_equal(p2$main_results$power, p$main_results$power)
expect_equal(p$pc_results$power, c(5,5,5))
})
#4b low power
test_that("4b", {
design <- ANOVA_design(design = "4b", n = 15,
mu = c(0, 0.25, 0.33, 0.44),
sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 15, tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$main_results$partial_eta_squared,
p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$pc_results$power,
c(10.14,14.08,21.39,5.51,7.94,5.98),
tolerance = 0.1)
})
#2x4 repeated measures
test_that("2b*4w", {
skip_on_cran()
design <- ANOVA_design(design = "2b*4w", n = 9,
mu = c(0.0, 0.0, 0.0, 0.0,
0, 0.5, 0.5, 0.5),
r = 0.71,
sd = 2, plot = FALSE)
set.seed(7224)
p <- ANOVA_exact(design, verbose = FALSE)
p22 <- ANOVA_exact2(design, verbose = FALSE)
set.seed(354186)
p2 <- ANOVA_power(design, nsims = 1000, verbose = FALSE)
expect_equal(p$main_results$power, c(7.1, 9.2, 9.2), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 1.5)
expect_equal(p$main_results$power, p22$main_results$power, tolerance = .08)
expect_equal(p$main_results$partial_eta_squared,
p22$main_results$partial_eta_squared, tolerance = .01)
expect_equal(p$manova_results$power, p22$manova_results$power, tolerance = 0.05)
expect_equal(p$manova_results$cohen_f, p22$manova_results$cohen_f, tolerance = 0.05)
})
#3w
test_that("3w", {
design <- ANOVA_design(design = "3w", n = 20,
mu = c(-0.3061862, 0.0000000, 0.3061862),
r = 0.8,
sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 96.9, tolerance = 0.05)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.02)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.02)
})
####Match Test results with appendices from SuperpowerBook
test_that("Aberson #1",{
design_result <- ANOVA_design(design = "4b",
n = 60,
sd = 10,
mu = c(80, 82, 82, 86),
labelnames = c("DORM",
"Control",
"T1",
"T2",
"T3"),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, 81.2, tolerance = 0.01)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
}
)
test_that("Aberson #2",{
design_result <- ANOVA_design(design = "2b*2b",
n = 100,
sd = 1.7,
mu = c(.85, .85,
0, .6),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(89.8,42.1,42.1), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
}
)
test_that("Aberson #3",{
design_result <- ANOVA_design(design = "2b*2b",
n = 250,
sd = 1.7,
mu = c(.85, .85,
0, .6),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(99.9,79.6,79.6), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
}
)
test_that("Aberson #4",{
design_result <- ANOVA_design(design = "4w",
n = 25, #25
sd = c(.4,.5,.6,.7),
mu = c(-.25, .00, .10, .15),
r = c(.50,
.30,
.15,
.5,
.30,
.50),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(80.9), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.025)
expect_equal(p$main_results$partial_eta_squared,
p2$main_results$partial_eta_squared, tolerance = 0.025)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.02)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
design_result <- ANOVA_design(design = "4w",
n = 25,
sd = c(.7),
mu = c(-.25, .00, .10, .15),
r = c(.50),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.02)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson #5",{
design_result <- ANOVA_design(design = "4w",
n = 100,
sd = c(.4,.5,2.5,2),
mu = c(-.25, .00, .10, .15),
r = c(.50,
.30,
.1,
.5,
.30,
.40),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(39.7), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.1)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.1)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.01)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson #6",{
design_result <- ANOVA_design(design = "2w*4w",
n = 80,
sd = c(.4,0.5,
2.5,2.0,
0.4,0.5,
2.5,2.0),
mu = c(-0.25,0.0,
0.10,0.15,
-0.25,0.10,
0.30,0.35),
r = c(.5),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(27.2,74.8,10.2), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.01)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson #7",{
design_result <- ANOVA_design("2b*4w",
n = 50,
sd = c(.4, .5, 0.6, .7,
.4, .5, .6, .7),
r = c(1.0,0.5,0.3,0.15,0.0,0.0,0.0,0.0,
0.5,1.0,0.5,0.3,0.0,0.0,0.0,0.0,
0.3,0.5,1.0,0.5,0.0,0.0,0.0,0.0,
0.15,0.3,0.5,1.0,0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0,1.0,0.5,0.3,0.15,
0.0,0.0,0.0,0.0,0.5,1.0,0.5,0.3,
0.0,0.0,0.0,0.0,0.3,0.5,1.0,0.5,
0.0,0.0,0.0,0.0,0.15,0.3,0.5,1.0),
mu = c(-.25, 0.0, 0.10, 0.15,
-.25,-.25,-.25,-.25),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose = FALSE)
p2 <- ANOVA_exact2(design_result,
verbose = FALSE)
expect_equal(p$main_results$power, c(86.4,82.7,82.7), tolerance = 0.01)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.01)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson Table 5.5",{
design_result <- Superpower::ANOVA_design("4b", sd = 10, n = 60, plot = FALSE,
mu = c(80,82,82,86))
power_result <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
expect_equal(round(power_result$emm_results$power, 1),c(87.4,12,17.9))
expect_equal(round(power_result$emm_results$power, 1),
round(power_result2$emm_results$power, 1))
expect_equal(round(power_result$emm_results$partial_eta_squared, 1),
round(power_result2$emm_results$partial_eta_squared, 1))
design_result <- Superpower::ANOVA_design("4b", sd = 10, n = 30, plot = FALSE,
mu = c(80,82,82,86))
power_result <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
expect_equal(round(power_result$main_results$power, 1),
round(power_result2$main_results$power, 1), tolerance = 0.05)
expect_equal(round(power_result$main_results$partial_eta_squared, 1),
round(power_result2$main_results$partial_eta_squared, 1), tolerance = 0.01)
expect_equal(round(power_result$emm_results$power, 1),
round(power_result2$emm_results$power, 1), tolerance = 0.05)
expect_equal(round(power_result$emm_results$partial_eta_squared, 1),
round(power_result2$emm_results$partial_eta_squared, 1), tolerance = 0.01)
})
test_that("Aberson Table 5.6",{
design_result <- Superpower::ANOVA_design("4b", sd = 10, n = 60, plot = FALSE,
mu = c(80,82,82,86))
power_result1 <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, alpha_level = .0085)
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, alpha_level = .0085)
expect_equal(round(power_result1$emm_results$power, 1),
c(6.1,6.1,73.6,.8,32.4,32.4))
expect_equal(power_result1$main_results$power,
power_result2$main_results$power,
tolerance = .01)
expect_equal(power_result1$main_results$partial_eta_squared,
power_result2$main_results$partial_eta_squared,
tolerance = .01)
expect_equal(power_result1$emm_results$power,
power_result2$emm_results$power,
tolerance = .01)
expect_equal(power_result1$emm_results$partial_eta_squared,
power_result2$emm_results$partial_eta_squared,
tolerance = .01)
})
test_that("Aberson Table 5.9",{
design_result <- Superpower::ANOVA_design("2b*2b", sd = 1.7, n = 250, plot = FALSE,
mu = c(.85,.85,0,.6))
power_result1 <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, emm_comp = "b|a")
power_result1a <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, emm_comp = "a|b")
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, emm_comp = "b|a")
power_simple <- round(c(power_result1$emm_results$power,
power_result1a$emm_results$power),1)
expect_equal(power_simple, c(5,97.6,100,37.6))
expect_equal(power_result1$main_results$power,
power_result2$main_results$power)
expect_equal(power_result1$main_results$partial_eta_squared,
power_result2$main_results$partial_eta_squared)
expect_equal(power_result1$emm_results$power,
power_result2$emm_results$power)
expect_equal(power_result1$emm_results$partial_eta_squared,
power_result2$emm_results$partial_eta_squared)
})
test_that("check lambda and verbose",{
hush=function(code){
sink("NUL") # use /dev/null in UNIX
tmp = code
sink()
return(tmp)
}
des <- ANOVA_design(
"2b*4w",
n = 50,
sd = c(2),
r = c(.45),
mu = c(-.25, 0.0, 0.10, 0.15,-.25, -.25, -.25, -.25),
plot = FALSE
)
res = hush(ANOVA_exact(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
res = hush(ANOVA_exact2(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
des <- ANOVA_design(
"2b*4w*3b",
n = 50,
sd = c(2),
r = c(.45),
mu = c(1:24),
plot = FALSE
)
expect_equal(as.vector(diag(as.matrix(des$sigmatrix))),
rep(4,24))
res = hush(ANOVA_exact(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
test = hush(print(res))
res = hush(ANOVA_exact2(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
test = hush(print(res))
})
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context("test-anova_exact")
# error messages
test_that("error messages", {
design <- ANOVA_design(design = "2b*4w",
n = 7,
mu = c(0,0,0,0,0.5,0.5,0.5,0.5),
sd = 1,
plot = FALSE)
expect_error(ANOVA_exact(), "argument \"design_result\" is missing, with no default")
expect_error(ANOVA_exact(design, verbose = FALSE),
fixed = TRUE)
expect_error(ANOVA_exact2())
design <- ANOVA_design(design = "2b*4w",
n = 75,
mu = c(0,0,0,0,0.5,0.5,0.5,0.5),
sd = 1,
plot = FALSE)
expect_error(ANOVA_exact2(design,
emm = TRUE,
emm_model = "NOT"))
expect_error(ANOVA_exact2(design,
emm = TRUE,
contrast_type = "NOT"))
expect_error(ANOVA_exact2(design,
emm = TRUE,
correction = "none1"))
expect_error(ANOVA_exact2(design,
emm = TRUE,
alpha_level = 1.05))
expect_error(ANOVA_exact(design,
emm = TRUE,
emm_model = "NOT"))
expect_error(ANOVA_exact(design,
emm = TRUE,
contrast_type = "NOT"))
expect_error(ANOVA_exact(design,
emm = TRUE,
correction = "none1"))
expect_error(ANOVA_exact(design,
emm = TRUE,
alpha_level = 1.05))
})
#2w null
test_that("2w null", {
design <- ANOVA_design(design = "2w", n = 100,
mu = c(0, 0),
sd = 1,
r = 0.5,
plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 = ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 5)
expect_equal(p$pc_results$power, 5)
expect_equal(p2$main_results, p$main_results)
# confint error
expect_error(confint(p))
})
#2b null
test_that("2b null", {
design <- ANOVA_design(design = "2b", n = 100, mu = c(0, 0), sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 = ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 5)
expect_equal(p$main_results$power, p2$main_results$power)
expect_equal(p$pc_results$power, 5)
})
#2w moderate effect
test_that("2w", {
design <- ANOVA_design(design = "2w", n = 21, mu = c(0, 0.65), sd = 1, r = 0.55, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 84.7, tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.1)
expect_equal(p$pc_results$power, 84.7, tolerance = 0.1)
})
#2b moderate effect
test_that("2b", {
design <- ANOVA_design(design = "2b", n = 22, mu = c(0, 0.65), sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 55.8, tolerance = 0.05)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$pc_results$power, 55.8, tolerance = 0.1)
})
#3w null
test_that("3w null", {
design <- ANOVA_design(design = "3w", n = 100,
mu = c(0, 0, 0), sd = 1, r = 0.5, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 5)
expect_equal(p2$main_results$power, p$main_results$power)
expect_equal(p$pc_results$power, c(5,5,5))
})
#4b low power
test_that("4b", {
design <- ANOVA_design(design = "4b", n = 15,
mu = c(0, 0.25, 0.33, 0.44),
sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 15, tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$main_results$partial_eta_squared,
p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$pc_results$power,
c(10.14,14.08,21.39,5.51,7.94,5.98),
tolerance = 0.1)
})
#2x4 repeated measures
test_that("2b*4w", {
skip_on_cran()
design <- ANOVA_design(design = "2b*4w", n = 9,
mu = c(0.0, 0.0, 0.0, 0.0,
0, 0.5, 0.5, 0.5),
r = 0.71,
sd = 2, plot = FALSE)
set.seed(7224)
p <- ANOVA_exact(design, verbose = FALSE)
p22 <- ANOVA_exact2(design, verbose = FALSE)
set.seed(354186)
p2 <- ANOVA_power(design, nsims = 1000, verbose = FALSE)
expect_equal(p$main_results$power, c(7.1, 9.2, 9.2), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 1.5)
expect_equal(p$main_results$power, p22$main_results$power, tolerance = .08)
expect_equal(p$main_results$partial_eta_squared,
p22$main_results$partial_eta_squared, tolerance = .01)
expect_equal(p$manova_results$power, p22$manova_results$power, tolerance = 0.05)
expect_equal(p$manova_results$cohen_f, p22$manova_results$cohen_f, tolerance = 0.05)
})
#3w
test_that("3w", {
design <- ANOVA_design(design = "3w", n = 20,
mu = c(-0.3061862, 0.0000000, 0.3061862),
r = 0.8,
sd = 1, plot = FALSE)
p <- ANOVA_exact(design, verbose = FALSE)
p2 <- ANOVA_exact2(design, verbose = FALSE)
expect_equal(p$main_results$power, 96.9, tolerance = 0.05)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.02)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.02)
})
####Match Test results with appendices from SuperpowerBook
test_that("Aberson #1",{
design_result <- ANOVA_design(design = "4b",
n = 60,
sd = 10,
mu = c(80, 82, 82, 86),
labelnames = c("DORM",
"Control",
"T1",
"T2",
"T3"),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, 81.2, tolerance = 0.01)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
}
)
test_that("Aberson #2",{
design_result <- ANOVA_design(design = "2b*2b",
n = 100,
sd = 1.7,
mu = c(.85, .85,
0, .6),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(89.8,42.1,42.1), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
}
)
test_that("Aberson #3",{
design_result <- ANOVA_design(design = "2b*2b",
n = 250,
sd = 1.7,
mu = c(.85, .85,
0, .6),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(99.9,79.6,79.6), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
}
)
test_that("Aberson #4",{
design_result <- ANOVA_design(design = "4w",
n = 25, #25
sd = c(.4,.5,.6,.7),
mu = c(-.25, .00, .10, .15),
r = c(.50,
.30,
.15,
.5,
.30,
.50),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(80.9), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.025)
expect_equal(p$main_results$partial_eta_squared,
p2$main_results$partial_eta_squared, tolerance = 0.025)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.02)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
design_result <- ANOVA_design(design = "4w",
n = 25,
sd = c(.7),
mu = c(-.25, .00, .10, .15),
r = c(.50),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.05)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.02)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson #5",{
design_result <- ANOVA_design(design = "4w",
n = 100,
sd = c(.4,.5,2.5,2),
mu = c(-.25, .00, .10, .15),
r = c(.50,
.30,
.1,
.5,
.30,
.40),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(39.7), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.1)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.1)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.01)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson #6",{
design_result <- ANOVA_design(design = "2w*4w",
n = 80,
sd = c(.4,0.5,
2.5,2.0,
0.4,0.5,
2.5,2.0),
mu = c(-0.25,0.0,
0.10,0.15,
-0.25,0.10,
0.30,0.35),
r = c(.5),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose=FALSE)
p2 <- ANOVA_exact2(design_result,
verbose=FALSE)
expect_equal(p$main_results$power, c(27.2,74.8,10.2), tolerance = 0.1)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.01)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson #7",{
design_result <- ANOVA_design("2b*4w",
n = 50,
sd = c(.4, .5, 0.6, .7,
.4, .5, .6, .7),
r = c(1.0,0.5,0.3,0.15,0.0,0.0,0.0,0.0,
0.5,1.0,0.5,0.3,0.0,0.0,0.0,0.0,
0.3,0.5,1.0,0.5,0.0,0.0,0.0,0.0,
0.15,0.3,0.5,1.0,0.0,0.0,0.0,0.0,
0.0,0.0,0.0,0.0,1.0,0.5,0.3,0.15,
0.0,0.0,0.0,0.0,0.5,1.0,0.5,0.3,
0.0,0.0,0.0,0.0,0.3,0.5,1.0,0.5,
0.0,0.0,0.0,0.0,0.15,0.3,0.5,1.0),
mu = c(-.25, 0.0, 0.10, 0.15,
-.25,-.25,-.25,-.25),
plot = FALSE)
p <- ANOVA_exact(design_result,
verbose = FALSE)
p2 <- ANOVA_exact2(design_result,
verbose = FALSE)
expect_equal(p$main_results$power, c(86.4,82.7,82.7), tolerance = 0.01)
expect_equal(p$main_results$power, p2$main_results$power, tolerance = 0.01)
expect_equal(p$main_results$partial_eta_squared, p2$main_results$partial_eta_squared, tolerance = 0.01)
expect_equal(p$manova_results$power, p2$manova_results$power, tolerance = 0.01)
expect_equal(p$manova_results$cohen_f, p2$manova_results$cohen_f, tolerance = 0.01)
}
)
test_that("Aberson Table 5.5",{
design_result <- Superpower::ANOVA_design("4b", sd = 10, n = 60, plot = FALSE,
mu = c(80,82,82,86))
power_result <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
expect_equal(round(power_result$emm_results$power, 1),c(87.4,12,17.9))
expect_equal(round(power_result$emm_results$power, 1),
round(power_result2$emm_results$power, 1))
expect_equal(round(power_result$emm_results$partial_eta_squared, 1),
round(power_result2$emm_results$partial_eta_squared, 1))
design_result <- Superpower::ANOVA_design("4b", sd = 10, n = 30, plot = FALSE,
mu = c(80,82,82,86))
power_result <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, contrast_type = "poly")
expect_equal(round(power_result$main_results$power, 1),
round(power_result2$main_results$power, 1), tolerance = 0.05)
expect_equal(round(power_result$main_results$partial_eta_squared, 1),
round(power_result2$main_results$partial_eta_squared, 1), tolerance = 0.01)
expect_equal(round(power_result$emm_results$power, 1),
round(power_result2$emm_results$power, 1), tolerance = 0.05)
expect_equal(round(power_result$emm_results$partial_eta_squared, 1),
round(power_result2$emm_results$partial_eta_squared, 1), tolerance = 0.01)
})
test_that("Aberson Table 5.6",{
design_result <- Superpower::ANOVA_design("4b", sd = 10, n = 60, plot = FALSE,
mu = c(80,82,82,86))
power_result1 <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, alpha_level = .0085)
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, alpha_level = .0085)
expect_equal(round(power_result1$emm_results$power, 1),
c(6.1,6.1,73.6,.8,32.4,32.4))
expect_equal(power_result1$main_results$power,
power_result2$main_results$power,
tolerance = .01)
expect_equal(power_result1$main_results$partial_eta_squared,
power_result2$main_results$partial_eta_squared,
tolerance = .01)
expect_equal(power_result1$emm_results$power,
power_result2$emm_results$power,
tolerance = .01)
expect_equal(power_result1$emm_results$partial_eta_squared,
power_result2$emm_results$partial_eta_squared,
tolerance = .01)
})
test_that("Aberson Table 5.9",{
design_result <- Superpower::ANOVA_design("2b*2b", sd = 1.7, n = 250, plot = FALSE,
mu = c(.85,.85,0,.6))
power_result1 <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, emm_comp = "b|a")
power_result1a <- Superpower::ANOVA_exact(design_result, verbose = FALSE,
emm = TRUE, emm_comp = "a|b")
power_result2 <- Superpower::ANOVA_exact2(design_result, verbose = FALSE,
emm = TRUE, emm_comp = "b|a")
power_simple <- round(c(power_result1$emm_results$power,
power_result1a$emm_results$power),1)
expect_equal(power_simple, c(5,97.6,100,37.6))
expect_equal(power_result1$main_results$power,
power_result2$main_results$power)
expect_equal(power_result1$main_results$partial_eta_squared,
power_result2$main_results$partial_eta_squared)
expect_equal(power_result1$emm_results$power,
power_result2$emm_results$power)
expect_equal(power_result1$emm_results$partial_eta_squared,
power_result2$emm_results$partial_eta_squared)
})
test_that("check lambda and verbose",{
hush=function(code){
sink("NUL") # use /dev/null in UNIX
tmp = code
sink()
return(tmp)
}
des <- ANOVA_design(
"2b*4w",
n = 50,
sd = c(2),
r = c(.45),
mu = c(-.25, 0.0, 0.10, 0.15,-.25, -.25, -.25, -.25),
plot = FALSE
)
res = hush(ANOVA_exact(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
res = hush(ANOVA_exact2(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
des <- ANOVA_design(
"2b*4w*3b",
n = 50,
sd = c(2),
r = c(.45),
mu = c(1:24),
plot = FALSE
)
expect_equal(as.vector(diag(as.matrix(des$sigmatrix))),
rep(4,24))
res = hush(ANOVA_exact(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
test = hush(print(res))
res = hush(ANOVA_exact2(design_result = des,
emm = TRUE,
verbose = TRUE,
liberal_lambda = TRUE))
test = hush(print(res))
})
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