tests/testthat/test-anova_design.R
In Lakens/ANOVApower: Simulation-Based Power Analysis for ANOVA Designs
context("test-anova_design")
# error messages ----
test_that("errors", {
# missing arguments
expect_error(ANOVA_design(),
"argument \"design\" is missing, with no default")
expect_error(ANOVA_design("2w*2b", n =20, sd = 1),
"argument \"mu\" is missing, with no default")
expect_error(ANOVA_design("2w*2b", mu = c(0, 0, 0, 0)),
"argument \"sd\" is missing, with no default")
expect_error(ANOVA_design("2w*2b", mu = c(0, 0, 0, 0), sd = 1),
"argument \"n\" is missing, with no default")
# passing bad arguments: *SHOULD BE AN ERROR*
expect_error(ANOVA_design("2w*2b", n = 100, mu = c(0, 0, 0, 0), sd = -1),
"Standard deviation (sd) is less than or equal to zero; input a value greater than zero", fixed = TRUE)
expect_error(ANOVA_design("2F", n = 10, mu = 1:2, sd = 1),
"Problem in the design argument: must input number of levels as integer (2-999) and factor-type (between or within) as lower case b (between) or w (within)",
fixed = TRUE)
expect_error(ANOVA_design("1001b", n = 10, mu = 1:1001, sd = 1),
"Problem in the design argument: must input number of levels as integer (2-999) and factor-type (between or within) as lower case b (between) or w (within)",
fixed = TRUE)
# bad arguments
expect_error(ANOVA_design("wrong design"),
"Problem in the design argument: must input number of levels as integer (2-999) and factor-type (between or within) as lower case b (between) or w (within)",
fixed = TRUE)
expect_error(ANOVA_design("2w*2b", n = "A", mu = 1:4, sd = 1),
"non-numeric argument to binary operator")
expect_error(ANOVA_design("2w*2b", n = 100, mu = c("A", "B", "C", "D"), sd = 1),
"non-numeric argument to binary operator")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = "A"),
"requires numeric/complex matrix/vector arguments")
expect_error(ANOVA_design("2w*2b", n = "A", mu = 1:4, sd = 1),
"non-numeric argument to binary operator")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, r = "A"),
"Correlation must be greater than -1 and less than 1",
fixed = TRUE)
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, labelnames = c("A", "B")),
"Variable 'design' does not match the length of the labelnames")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1,
labelnames = c("W factor", "W 1", "W 2", "B factor", "B 1", "B 2")),
"unexpected symbol")
# inconsistent arguments
expect_error(ANOVA_design("2w*2b", n = 100, mu = 0, sd = 1),
"the length of the vector with means does not match the study design")
#expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = c(1,2)),
# "The SD must be a length of 1 or match the length of the study design")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = c(1,1)),
"the length of sd_for_sigma must be 1 or vars")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, r = c(.5, 0, .4)),
"object 'cor_mat' not found")
})
# test_that("2W", {
# # fix uppercase letters are design = 0
# d <- ANOVA_design("2W", n = 100, mu = c(0,0), sd = 1)
# expect_equal(d$design, 1)
# })
#
# # test grep for strings ----
# test_that("test grep for strings", {
# pattern <- "^([2-9](w|b)\\*){0,2}[2-9](w|b)$"
#
# # should work
# good_strings <- c("2w", "2b", "2W", "2B", "2w*2b", "3w*3b*2w")
# for (x in good_strings) {
# find <- grep(pattern, x, ignore.case = TRUE, perl = TRUE)
# #expect_equal(find, 1)
# if (length(find) == 0 || find != 1) { print(x) }
# }
#
#
# # should not work
# bad_strings <- c("2a", "w2", "b2", "0w", "0b", "1w", "1b", "2b+2w", "2b*2b*2b*2b")
# for (x in bad_strings) {
# find <- grep(pattern, x, ignore.case = TRUE, perl = TRUE)
# #expect_equal(find, integer(0))
# if (length(find) != 0) { print(x) }
# }
# })
# 2w defaults ----
test_that("2w defaults", {
d <- ANOVA_design("2w", n = 100, mu = c(0,0), sd = 1, plot = FALSE)
expect_equal(d$design_factors, 1)
expect_equal(d$design_list, c("a1", "a2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ a + Error(subject/a))
expect_equal(d$frml2, ~a)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0)
expect_equal(d$n, 100)
mat <- data.frame(
"a1" = c(1, 0),
"a2" = c(0, 1),
row.names = c("a1", "a2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2w")
expect_equal(d$labelnameslist, list(c("a1", "a2")))
expect_equal(d$factornames, "a")
})
# 2b defaults----
test_that("2b defaults", {
d <- ANOVA_design("2b", n = 100, mu = c(0,0), sd = 1, plot = FALSE)
expect_equal(d$design_factors, 0)
expect_equal(d$design_list, c("a1", "a2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ a + Error(1 | subject))
expect_equal(d$frml2, ~a)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0)
expect_equal(d$n, 100)
mat <- data.frame(
"a1" = c(1, 0),
"a2" = c(0, 1),
row.names = c("a1", "a2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b")
expect_equal(d$labelnameslist, list(c("a1", "a2")))
expect_equal(d$factornames, "a")
})
# 2w set r & labels ----
test_that("2w set r & labels", {
d <- ANOVA_design("2w", n = 100, mu = c(0,0), sd = 1, r = 0.5, labelnames = c("W", "W1", "W2"), plot = FALSE)
expect_equal(d$design_factors, 1)
expect_equal(d$design_list, c("W1", "W2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ W + Error(subject/W))
expect_equal(d$frml2, ~W)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"W1" = c(1, 0.5),
"W2" = c(0.5, 1),
row.names = c("W1", "W2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2w")
expect_equal(d$labelnameslist, list(c("W1", "W2")))
expect_equal(d$factornames, "W")
})
# 2b set r & labels----
test_that("2b set r & labels", {
d <- ANOVA_design("2b", n = 100, mu = c(0,0), sd = 1, r = 0.5, labelnames = c("B", "B1", "B2"), plot = FALSE)
expect_equal(d$design_factors, 0)
expect_equal(d$design_list, c("B1", "B2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ B + Error(1 | subject))
expect_equal(d$frml2, ~B)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"B1" = c(1, 0),
"B2" = c(0, 1),
row.names = c("B1", "B2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b")
expect_equal(d$labelnameslist, list(c("B1", "B2")))
expect_equal(d$factornames, "B")
})
# 4w
test_that("4w", {
d <- ANOVA_design("4w", n = 100, mu = 1:4, sd = 1:4, r = 0.5,
labelnames = c("W", "W1", "W2", "W3", "W4"), plot = FALSE)
expect_equal(d$design_factors, 1)
expect_equal(d$design_list, c("W1", "W2", "W3", "W4"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ W + Error(subject/W))
expect_equal(d$frml2, ~W)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1:4)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"W1" = c(1, 0.5, 0.5, 0.5),
"W2" = c(0.5, 1, 0.5, 0.5),
"W3" = c(0.5, 0.5, 1, 0.5),
"W4" = c(0.5, 0.5, 0.5, 1),
row.names = c("W1", "W2", "W3", "W4")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
sigma <- as.matrix(mat) * (1:4 %*% t(1:4))
expect_true(dplyr::all_equal(d$sigmatrix, as.data.frame(sigma)))
expect_equal(d$design, "4w")
expect_equal(d$labelnameslist, list(c("W1", "W2", "W3", "W4")))
expect_equal(d$factornames, "W")
})
# 4b
test_that("4b", {
d <- ANOVA_design("4b", n = 100, mu = 1:4, sd = 1:4, r = 0.5,
labelnames = c("B", "B1", "B2", "B3", "B4"), plot = FALSE)
expect_equal(d$design_factors, 0)
expect_equal(d$design_list, c("B1", "B2", "B3", "B4"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ B + Error(1 | subject))
expect_equal(d$frml2, ~B)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1:4)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"B1" = c(1, 0, 0, 0),
"B2" = c(0, 1, 0, 0),
"B3" = c(0, 0, 1, 0),
"B4" = c(0, 0, 0, 1),
row.names = c("B1", "B2", "B3", "B4")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
sigma <- as.matrix(mat) * (1:4 %*% t(1:4))
expect_true(dplyr::all_equal(d$sigmatrix, as.data.frame(sigma)))
expect_equal(d$design, "4b")
expect_equal(d$labelnameslist, list(c("B1", "B2", "B3", "B4")))
expect_equal(d$factornames, "B")
})
# 2w*2b----
test_that("2w*2b", {
d <- ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, r = 0.5,
labelnames = c("W", "W1", "W2", "B", "B1", "B2"), plot = FALSE)
expect_equal(d$design_factors, c(1, 0))
expect_equal(d$design_list, c("W1_B1", "W1_B2", "W2_B1", "W2_B2"))
expect_equal(d$factors, 2)
expect_equal(d$frml1, y ~ W * B + Error(subject/W))
expect_equal(d$frml2, ~W + B)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"W1_B1" = c(1, .5, 0, 0),
"W2_B1" = c(.5, 1, 0, 0),
"W1_B2" = c(0, 0, 1, .5),
"W2_B2" = c(0, 0, .5, 1),
row.names = c("W1_B1", "W2_B1", "W1_B2", "W2_B2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2w*2b")
expect_equal(d$labelnameslist, list(c("W1", "W2"), c("B1", "B2")))
expect_equal(d$factornames, c("W", "B"))
})
# 2b*2w----
test_that("2b*2w", {
d <- ANOVA_design("2b*2w", n = 100, mu = 1:4, sd = 1, r = 0.5,
labelnames = c("B", "B1", "B2", "W", "W1", "W2"), plot = FALSE)
expect_equal(d$design_factors, c(0, 1))
expect_equal(d$design_list, c("B1_W1", "B1_W2", "B2_W1", "B2_W2"))
expect_equal(d$factors, 2)
expect_equal(d$frml1, y ~ B * W + Error(subject/W))
expect_equal(d$frml2, ~B + W)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"B1_W1" = c(1, 0, .5, 0),
"B2_W1" = c(0, 1, 0, .5),
"B1_W2" = c(.5, 0, 1, 0),
"B2_W2" = c(0, .5, 0, 1),
row.names = c("B1_W1", "B2_W1", "B1_W2", "B2_W2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b*2w")
expect_equal(d$labelnameslist, list(c("B1", "B2"), c("W1", "W2")))
expect_equal(d$factornames, c("B", "W"))
})
#Add three way designs
test_that("2b*2b*2b", {
d <- ANOVA_design("2b*2b*2b", n = 100, mu = 1:8, sd = 1, plot = FALSE)
expect_equal(d$design_factors, c(0, 0, 0))
expect_equal(d$design_list, c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_equal(d$factors, 3)
expect_equal(d$frml1, y ~ a * b * c + Error(1 | subject))
expect_equal(d$frml2, ~ a + b + c)
expect_equal(d$mu, 1:8)
expect_equal(d$sd, 1)
expect_equal(d$n, 100)
mat <- data.frame(
"a1_b1_c1" = c(1, 0, 0, 0, 0, 0, 0, 0),
"a1_b1_c2" = c(0, 1, 0, 0, 0, 0, 0, 0),
"a1_b2_c1" = c(0, 0, 1, 0, 0, 0, 0, 0),
"a1_b2_c2" = c(0, 0, 0, 1, 0, 0, 0, 0),
"a2_b1_c1" = c(0, 0, 0, 0, 1, 0, 0, 0),
"a2_b1_c2" = c(0, 0, 0, 0, 0, 1, 0, 0),
"a2_b2_c1" = c(0, 0, 0, 0, 0, 0, 1, 0),
"a2_b2_c2" = c(0, 0, 0, 0, 0, 0, 0, 1),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b*2b*2b")
})
test_that("2w*2w*2w", {
d <- ANOVA_design("2w*2w*2w", n = 100, mu = 1:8, sd = 2, r = .65, plot = FALSE)
expect_equal(d$design_factors, c(1, 1, 1))
expect_equal(d$design_list, c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_equal(d$factors, 3)
expect_equal(d$frml1, y ~ a * b * c + Error(subject/a * b * c))
expect_equal(d$frml2, ~ a + b + c)
expect_equal(d$mu, 1:8)
expect_equal(d$sd, 2)
expect_equal(d$n, 100)
expect_equal(d$r, 0.65)
mat <- data.frame(
"a1_b1_c1" = c(1.00, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65),
"a1_b1_c2" = c(0.65, 1.00, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65),
"a1_b2_c1" = c(0.65, 0.65, 1.00, 0.65, 0.65, 0.65, 0.65, 0.65),
"a1_b2_c2" = c(0.65, 0.65, 0.65, 1.00, 0.65, 0.65, 0.65, 0.65),
"a2_b1_c1" = c(0.65, 0.65, 0.65, 0.65, 1.00, 0.65, 0.65, 0.65),
"a2_b1_c2" = c(0.65, 0.65, 0.65, 0.65, 0.65, 1.00, 0.65, 0.65),
"a2_b2_c1" = c(0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 1.00, 0.65),
"a2_b2_c2" = c(0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 1.00),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$cor_mat, mat))
var <- (2)^2
covar <- var*as.numeric(0.65)
sig_mat <- data.frame(
"a1_b1_c1" = c(var, covar, covar, covar, covar, covar, covar, covar),
"a1_b1_c2" = c(covar, var, covar, covar, covar, covar, covar, covar),
"a1_b2_c1" = c(covar, covar, var, covar, covar, covar, covar, covar),
"a1_b2_c2" = c(covar, covar, covar, var, covar, covar, covar, covar),
"a2_b1_c1" = c(covar, covar, covar, covar, var, covar, covar, covar),
"a2_b1_c2" = c(covar, covar, covar, covar, covar, var, covar, covar),
"a2_b2_c1" = c(covar, covar, covar, covar, covar, covar, var, covar),
"a2_b2_c2" = c(covar, covar, covar, covar, covar, covar, covar, var),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$sigmatrix, sig_mat))
expect_equal(d$design, "2w*2w*2w")
})
test_that("2b*2b*2w", {
d <- ANOVA_design("2b*2b*2w", n = 100, mu = 1:8, sd = 1.5, r = .68, plot = FALSE)
expect_equal(d$design_factors, c(0, 0, 1))
expect_equal(d$design_list, c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_equal(d$factors, 3)
expect_equal(d$frml1, y ~ a * b * c + Error(subject/c))
expect_equal(d$frml2, ~ a + b + c)
expect_equal(d$mu, 1:8)
expect_equal(d$sd, 1.5)
expect_equal(d$n, 100)
expect_equal(d$r, 0.68)
mat <- data.frame(
"a1_b1_c1" = c(1.00, 0.68, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00),
"a1_b1_c2" = c(0.68, 1.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00),
"a1_b2_c1" = c(0.00, 0.00, 1.00, 0.68, 0.00, 0.00, 0.00, 0.00),
"a1_b2_c2" = c(0.00, 0.00, 0.68, 1.00, 0.00, 0.00, 0.00, 0.00),
"a2_b1_c1" = c(0.00, 0.00, 0.00, 0.00, 1.00, 0.68, 0.00, 0.00),
"a2_b1_c2" = c(0.00, 0.00, 0.00, 0.00, 0.68, 1.00, 0.00, 0.00),
"a2_b2_c1" = c(0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 1.00, 0.68),
"a2_b2_c2" = c(0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.68, 1.00),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$cor_mat, mat))
sig_mat <- mat
sig_mat[mat == 0.68] <- (1.5^2)*0.68
sig_mat[mat == 1.00] <- (1.5^2)
expect_true(dplyr::all_equal(d$sigmatrix, sig_mat))
expect_equal(d$design, "2b*2b*2w")
})
Lakens/ANOVApower documentation built on Jan. 9, 2020, 5:32 p.m.
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context("test-anova_design")
# error messages ----
test_that("errors", {
# missing arguments
expect_error(ANOVA_design(),
"argument \"design\" is missing, with no default")
expect_error(ANOVA_design("2w*2b", n =20, sd = 1),
"argument \"mu\" is missing, with no default")
expect_error(ANOVA_design("2w*2b", mu = c(0, 0, 0, 0)),
"argument \"sd\" is missing, with no default")
expect_error(ANOVA_design("2w*2b", mu = c(0, 0, 0, 0), sd = 1),
"argument \"n\" is missing, with no default")
# passing bad arguments: *SHOULD BE AN ERROR*
expect_error(ANOVA_design("2w*2b", n = 100, mu = c(0, 0, 0, 0), sd = -1),
"Standard deviation (sd) is less than or equal to zero; input a value greater than zero", fixed = TRUE)
expect_error(ANOVA_design("2F", n = 10, mu = 1:2, sd = 1),
"Problem in the design argument: must input number of levels as integer (2-999) and factor-type (between or within) as lower case b (between) or w (within)",
fixed = TRUE)
expect_error(ANOVA_design("1001b", n = 10, mu = 1:1001, sd = 1),
"Problem in the design argument: must input number of levels as integer (2-999) and factor-type (between or within) as lower case b (between) or w (within)",
fixed = TRUE)
# bad arguments
expect_error(ANOVA_design("wrong design"),
"Problem in the design argument: must input number of levels as integer (2-999) and factor-type (between or within) as lower case b (between) or w (within)",
fixed = TRUE)
expect_error(ANOVA_design("2w*2b", n = "A", mu = 1:4, sd = 1),
"non-numeric argument to binary operator")
expect_error(ANOVA_design("2w*2b", n = 100, mu = c("A", "B", "C", "D"), sd = 1),
"non-numeric argument to binary operator")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = "A"),
"requires numeric/complex matrix/vector arguments")
expect_error(ANOVA_design("2w*2b", n = "A", mu = 1:4, sd = 1),
"non-numeric argument to binary operator")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, r = "A"),
"Correlation must be greater than -1 and less than 1",
fixed = TRUE)
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, labelnames = c("A", "B")),
"Variable 'design' does not match the length of the labelnames")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1,
labelnames = c("W factor", "W 1", "W 2", "B factor", "B 1", "B 2")),
"unexpected symbol")
# inconsistent arguments
expect_error(ANOVA_design("2w*2b", n = 100, mu = 0, sd = 1),
"the length of the vector with means does not match the study design")
#expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = c(1,2)),
# "The SD must be a length of 1 or match the length of the study design")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = c(1,1)),
"the length of sd_for_sigma must be 1 or vars")
expect_error(ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, r = c(.5, 0, .4)),
"object 'cor_mat' not found")
})
# test_that("2W", {
# # fix uppercase letters are design = 0
# d <- ANOVA_design("2W", n = 100, mu = c(0,0), sd = 1)
# expect_equal(d$design, 1)
# })
#
# # test grep for strings ----
# test_that("test grep for strings", {
# pattern <- "^([2-9](w|b)\\*){0,2}[2-9](w|b)$"
#
# # should work
# good_strings <- c("2w", "2b", "2W", "2B", "2w*2b", "3w*3b*2w")
# for (x in good_strings) {
# find <- grep(pattern, x, ignore.case = TRUE, perl = TRUE)
# #expect_equal(find, 1)
# if (length(find) == 0 || find != 1) { print(x) }
# }
#
#
# # should not work
# bad_strings <- c("2a", "w2", "b2", "0w", "0b", "1w", "1b", "2b+2w", "2b*2b*2b*2b")
# for (x in bad_strings) {
# find <- grep(pattern, x, ignore.case = TRUE, perl = TRUE)
# #expect_equal(find, integer(0))
# if (length(find) != 0) { print(x) }
# }
# })
# 2w defaults ----
test_that("2w defaults", {
d <- ANOVA_design("2w", n = 100, mu = c(0,0), sd = 1, plot = FALSE)
expect_equal(d$design_factors, 1)
expect_equal(d$design_list, c("a1", "a2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ a + Error(subject/a))
expect_equal(d$frml2, ~a)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0)
expect_equal(d$n, 100)
mat <- data.frame(
"a1" = c(1, 0),
"a2" = c(0, 1),
row.names = c("a1", "a2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2w")
expect_equal(d$labelnameslist, list(c("a1", "a2")))
expect_equal(d$factornames, "a")
})
# 2b defaults----
test_that("2b defaults", {
d <- ANOVA_design("2b", n = 100, mu = c(0,0), sd = 1, plot = FALSE)
expect_equal(d$design_factors, 0)
expect_equal(d$design_list, c("a1", "a2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ a + Error(1 | subject))
expect_equal(d$frml2, ~a)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0)
expect_equal(d$n, 100)
mat <- data.frame(
"a1" = c(1, 0),
"a2" = c(0, 1),
row.names = c("a1", "a2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b")
expect_equal(d$labelnameslist, list(c("a1", "a2")))
expect_equal(d$factornames, "a")
})
# 2w set r & labels ----
test_that("2w set r & labels", {
d <- ANOVA_design("2w", n = 100, mu = c(0,0), sd = 1, r = 0.5, labelnames = c("W", "W1", "W2"), plot = FALSE)
expect_equal(d$design_factors, 1)
expect_equal(d$design_list, c("W1", "W2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ W + Error(subject/W))
expect_equal(d$frml2, ~W)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"W1" = c(1, 0.5),
"W2" = c(0.5, 1),
row.names = c("W1", "W2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2w")
expect_equal(d$labelnameslist, list(c("W1", "W2")))
expect_equal(d$factornames, "W")
})
# 2b set r & labels----
test_that("2b set r & labels", {
d <- ANOVA_design("2b", n = 100, mu = c(0,0), sd = 1, r = 0.5, labelnames = c("B", "B1", "B2"), plot = FALSE)
expect_equal(d$design_factors, 0)
expect_equal(d$design_list, c("B1", "B2"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ B + Error(1 | subject))
expect_equal(d$frml2, ~B)
expect_equal(d$mu, c(0, 0))
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"B1" = c(1, 0),
"B2" = c(0, 1),
row.names = c("B1", "B2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b")
expect_equal(d$labelnameslist, list(c("B1", "B2")))
expect_equal(d$factornames, "B")
})
# 4w
test_that("4w", {
d <- ANOVA_design("4w", n = 100, mu = 1:4, sd = 1:4, r = 0.5,
labelnames = c("W", "W1", "W2", "W3", "W4"), plot = FALSE)
expect_equal(d$design_factors, 1)
expect_equal(d$design_list, c("W1", "W2", "W3", "W4"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ W + Error(subject/W))
expect_equal(d$frml2, ~W)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1:4)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"W1" = c(1, 0.5, 0.5, 0.5),
"W2" = c(0.5, 1, 0.5, 0.5),
"W3" = c(0.5, 0.5, 1, 0.5),
"W4" = c(0.5, 0.5, 0.5, 1),
row.names = c("W1", "W2", "W3", "W4")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
sigma <- as.matrix(mat) * (1:4 %*% t(1:4))
expect_true(dplyr::all_equal(d$sigmatrix, as.data.frame(sigma)))
expect_equal(d$design, "4w")
expect_equal(d$labelnameslist, list(c("W1", "W2", "W3", "W4")))
expect_equal(d$factornames, "W")
})
# 4b
test_that("4b", {
d <- ANOVA_design("4b", n = 100, mu = 1:4, sd = 1:4, r = 0.5,
labelnames = c("B", "B1", "B2", "B3", "B4"), plot = FALSE)
expect_equal(d$design_factors, 0)
expect_equal(d$design_list, c("B1", "B2", "B3", "B4"))
expect_equal(d$factors, 1)
expect_equal(d$frml1, y ~ B + Error(1 | subject))
expect_equal(d$frml2, ~B)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1:4)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"B1" = c(1, 0, 0, 0),
"B2" = c(0, 1, 0, 0),
"B3" = c(0, 0, 1, 0),
"B4" = c(0, 0, 0, 1),
row.names = c("B1", "B2", "B3", "B4")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
sigma <- as.matrix(mat) * (1:4 %*% t(1:4))
expect_true(dplyr::all_equal(d$sigmatrix, as.data.frame(sigma)))
expect_equal(d$design, "4b")
expect_equal(d$labelnameslist, list(c("B1", "B2", "B3", "B4")))
expect_equal(d$factornames, "B")
})
# 2w*2b----
test_that("2w*2b", {
d <- ANOVA_design("2w*2b", n = 100, mu = 1:4, sd = 1, r = 0.5,
labelnames = c("W", "W1", "W2", "B", "B1", "B2"), plot = FALSE)
expect_equal(d$design_factors, c(1, 0))
expect_equal(d$design_list, c("W1_B1", "W1_B2", "W2_B1", "W2_B2"))
expect_equal(d$factors, 2)
expect_equal(d$frml1, y ~ W * B + Error(subject/W))
expect_equal(d$frml2, ~W + B)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"W1_B1" = c(1, .5, 0, 0),
"W2_B1" = c(.5, 1, 0, 0),
"W1_B2" = c(0, 0, 1, .5),
"W2_B2" = c(0, 0, .5, 1),
row.names = c("W1_B1", "W2_B1", "W1_B2", "W2_B2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2w*2b")
expect_equal(d$labelnameslist, list(c("W1", "W2"), c("B1", "B2")))
expect_equal(d$factornames, c("W", "B"))
})
# 2b*2w----
test_that("2b*2w", {
d <- ANOVA_design("2b*2w", n = 100, mu = 1:4, sd = 1, r = 0.5,
labelnames = c("B", "B1", "B2", "W", "W1", "W2"), plot = FALSE)
expect_equal(d$design_factors, c(0, 1))
expect_equal(d$design_list, c("B1_W1", "B1_W2", "B2_W1", "B2_W2"))
expect_equal(d$factors, 2)
expect_equal(d$frml1, y ~ B * W + Error(subject/W))
expect_equal(d$frml2, ~B + W)
expect_equal(d$mu, 1:4)
expect_equal(d$sd, 1)
expect_equal(d$r, 0.5)
expect_equal(d$n, 100)
mat <- data.frame(
"B1_W1" = c(1, 0, .5, 0),
"B2_W1" = c(0, 1, 0, .5),
"B1_W2" = c(.5, 0, 1, 0),
"B2_W2" = c(0, .5, 0, 1),
row.names = c("B1_W1", "B2_W1", "B1_W2", "B2_W2")
)
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b*2w")
expect_equal(d$labelnameslist, list(c("B1", "B2"), c("W1", "W2")))
expect_equal(d$factornames, c("B", "W"))
})
#Add three way designs
test_that("2b*2b*2b", {
d <- ANOVA_design("2b*2b*2b", n = 100, mu = 1:8, sd = 1, plot = FALSE)
expect_equal(d$design_factors, c(0, 0, 0))
expect_equal(d$design_list, c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_equal(d$factors, 3)
expect_equal(d$frml1, y ~ a * b * c + Error(1 | subject))
expect_equal(d$frml2, ~ a + b + c)
expect_equal(d$mu, 1:8)
expect_equal(d$sd, 1)
expect_equal(d$n, 100)
mat <- data.frame(
"a1_b1_c1" = c(1, 0, 0, 0, 0, 0, 0, 0),
"a1_b1_c2" = c(0, 1, 0, 0, 0, 0, 0, 0),
"a1_b2_c1" = c(0, 0, 1, 0, 0, 0, 0, 0),
"a1_b2_c2" = c(0, 0, 0, 1, 0, 0, 0, 0),
"a2_b1_c1" = c(0, 0, 0, 0, 1, 0, 0, 0),
"a2_b1_c2" = c(0, 0, 0, 0, 0, 1, 0, 0),
"a2_b2_c1" = c(0, 0, 0, 0, 0, 0, 1, 0),
"a2_b2_c2" = c(0, 0, 0, 0, 0, 0, 0, 1),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$cor_mat, mat))
expect_true(dplyr::all_equal(d$sigmatrix, mat))
expect_equal(d$design, "2b*2b*2b")
})
test_that("2w*2w*2w", {
d <- ANOVA_design("2w*2w*2w", n = 100, mu = 1:8, sd = 2, r = .65, plot = FALSE)
expect_equal(d$design_factors, c(1, 1, 1))
expect_equal(d$design_list, c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_equal(d$factors, 3)
expect_equal(d$frml1, y ~ a * b * c + Error(subject/a * b * c))
expect_equal(d$frml2, ~ a + b + c)
expect_equal(d$mu, 1:8)
expect_equal(d$sd, 2)
expect_equal(d$n, 100)
expect_equal(d$r, 0.65)
mat <- data.frame(
"a1_b1_c1" = c(1.00, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65),
"a1_b1_c2" = c(0.65, 1.00, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65),
"a1_b2_c1" = c(0.65, 0.65, 1.00, 0.65, 0.65, 0.65, 0.65, 0.65),
"a1_b2_c2" = c(0.65, 0.65, 0.65, 1.00, 0.65, 0.65, 0.65, 0.65),
"a2_b1_c1" = c(0.65, 0.65, 0.65, 0.65, 1.00, 0.65, 0.65, 0.65),
"a2_b1_c2" = c(0.65, 0.65, 0.65, 0.65, 0.65, 1.00, 0.65, 0.65),
"a2_b2_c1" = c(0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 1.00, 0.65),
"a2_b2_c2" = c(0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 0.65, 1.00),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$cor_mat, mat))
var <- (2)^2
covar <- var*as.numeric(0.65)
sig_mat <- data.frame(
"a1_b1_c1" = c(var, covar, covar, covar, covar, covar, covar, covar),
"a1_b1_c2" = c(covar, var, covar, covar, covar, covar, covar, covar),
"a1_b2_c1" = c(covar, covar, var, covar, covar, covar, covar, covar),
"a1_b2_c2" = c(covar, covar, covar, var, covar, covar, covar, covar),
"a2_b1_c1" = c(covar, covar, covar, covar, var, covar, covar, covar),
"a2_b1_c2" = c(covar, covar, covar, covar, covar, var, covar, covar),
"a2_b2_c1" = c(covar, covar, covar, covar, covar, covar, var, covar),
"a2_b2_c2" = c(covar, covar, covar, covar, covar, covar, covar, var),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$sigmatrix, sig_mat))
expect_equal(d$design, "2w*2w*2w")
})
test_that("2b*2b*2w", {
d <- ANOVA_design("2b*2b*2w", n = 100, mu = 1:8, sd = 1.5, r = .68, plot = FALSE)
expect_equal(d$design_factors, c(0, 0, 1))
expect_equal(d$design_list, c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_equal(d$factors, 3)
expect_equal(d$frml1, y ~ a * b * c + Error(subject/c))
expect_equal(d$frml2, ~ a + b + c)
expect_equal(d$mu, 1:8)
expect_equal(d$sd, 1.5)
expect_equal(d$n, 100)
expect_equal(d$r, 0.68)
mat <- data.frame(
"a1_b1_c1" = c(1.00, 0.68, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00),
"a1_b1_c2" = c(0.68, 1.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00),
"a1_b2_c1" = c(0.00, 0.00, 1.00, 0.68, 0.00, 0.00, 0.00, 0.00),
"a1_b2_c2" = c(0.00, 0.00, 0.68, 1.00, 0.00, 0.00, 0.00, 0.00),
"a2_b1_c1" = c(0.00, 0.00, 0.00, 0.00, 1.00, 0.68, 0.00, 0.00),
"a2_b1_c2" = c(0.00, 0.00, 0.00, 0.00, 0.68, 1.00, 0.00, 0.00),
"a2_b2_c1" = c(0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 1.00, 0.68),
"a2_b2_c2" = c(0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.68, 1.00),
row.names = c("a1_b1_c1", "a1_b1_c2", "a1_b2_c1", "a1_b2_c2", "a2_b1_c1", "a2_b1_c2", "a2_b2_c1", "a2_b2_c2"))
expect_true(dplyr::all_equal(d$cor_mat, mat))
sig_mat <- mat
sig_mat[mat == 0.68] <- (1.5^2)*0.68
sig_mat[mat == 1.00] <- (1.5^2)
expect_true(dplyr::all_equal(d$sigmatrix, sig_mat))
expect_equal(d$design, "2b*2b*2w")
})
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