Nothing
test_that("estimate_rdiff_two compared to ESCI_Two_Correlations, summary data", {
# Underlying CI approach has changed, so CIs no longer match
# this test checks against values provided from
# statpsych
estimate <- esci::estimate_rdiff_two(
comparison_r = .53,
comparison_n = 47,
reference_r = .41,
reference_n = 59,
grouping_variable_levels = c("Females", "Males"),
x_variable_name = "Satisfaction with life",
y_variable_name = "Body satisfaction",
grouping_variable_name = "Gender",
conf_level = .95
)
r1 <- as.list(
as.data.frame(
statpsych::ci.cor(
alpha = 1 - 0.95,
cor = .53,
s = 0,
n = 47
)
)
)
r2 <- as.list(
as.data.frame(
statpsych::ci.cor(
alpha = 1 - 0.95,
cor = .41,
s = 0,
n = 59
)
)
)
mysp <- as.list(
as.data.frame(
statpsych::ci.cor2(
alpha = 1 - 0.95,
cor1 = 0.53,
cor2 = 0.41,
n1 = 47,
n2 = 59
)
)
)
testthat::expect_s3_class(estimate, "esci_estimate")
testthat::expect_snapshot(estimate)
testthat::expect_equal(estimate$es_r$effect_size[[1]], r2$Estimate)
testthat::expect_equal(estimate$es_r$LL[[1]], r2$LL)
testthat::expect_equal(estimate$es_r$UL[[1]], r2$UL)
testthat::expect_equal(estimate$es_r$SE[[1]], r2$SE)
testthat::expect_equal(estimate$es_r$effect_size[[2]], r1$Estimate)
testthat::expect_equal(estimate$es_r$LL[[2]], r1$LL)
testthat::expect_equal(estimate$es_r$UL[[2]], r1$UL)
testthat::expect_equal(estimate$es_r$SE[[2]], r1$SE)
testthat::expect_equal(estimate$es_r_difference$effect_size[[3]], mysp$Estimate)
testthat::expect_equal(estimate$es_r_difference$LL[[3]], mysp$LL)
testthat::expect_equal(estimate$es_r_difference$UL[[3]], mysp$UL)
suppressWarnings(myplot <- esci::plot_correlation(estimate))
testthat::expect_s3_class(myplot, "ggplot")
})
test_that("estimate_rdiff_two of from Thomason1, ESCI_Scatterplots", {
thomason1 <- data.frame(
ls_pre = c(
13,
12,
12,
9,
14,
17,
14,
9,
6,
7,
11,
15
),
ls_post = c(
14,
13,
16,
12,
15,
18,
13,
10,
10,
8,
14,
16
),
major = c(
"Humanities",
"Humanities",
"Humanities",
"Humanities",
"Humanities",
"Humanities",
"Science",
"Science",
"Science",
"Science",
"Science",
"Science"
)
)
thomason1$major <- as.factor(thomason1$major)
estimate <- esci::estimate_rdiff_two(
thomason1,
ls_pre,
ls_post,
major
)
mysp <- as.list(
as.data.frame(
statpsych::ci.cor2(
alpha = 1 - 0.95,
cor1 = estimate$es_r$effect_size[[2]],
cor2 = estimate$es_r$effect_size[[1]],
n1 = estimate$es_r$n[[2]],
n2 = estimate$es_r$n[[1]]
)
)
)
testthat::expect_snapshot(estimate)
testthat::expect_equal(estimate$es_r_difference$effect_size[[3]], mysp$Estimate)
testthat::expect_equal(estimate$es_r_difference$LL[[3]], mysp$LL)
testthat::expect_equal(estimate$es_r_difference$UL[[3]], mysp$UL)
suppressWarnings(try(myplot <- esci::plot_rdiff(estimate), silent = TRUE))
testthat::expect_s3_class(myplot, "ggplot")
suppressWarnings(splot <- esci::plot_scatter(estimate))
testthat::expect_s3_class(splot, "ggplot")
})
test_that("Compare estimate_rdiff_two to statpsych::ci.cor", {
myconfs <- c(0.95, 0.99)
myrs <- seq(from = -0.90, to = 0.90, by = 0.5)
myr2s <- seq(from = -0.90, to = 0.90, by = 0.5)
myns <- seq(from = 5, to = 105, by = 45)
for (myn in myns) {
for (myconf_level in myconfs) {
for (myr in myrs) {
for (myr2 in myr2s) {
suppressWarnings(
estimate <- esci::estimate_rdiff_two(
comparison_r = myr,
comparison_n = myn,
reference_r = myr2,
reference_n = myn + 5,
grouping_variable_levels = c("Females", "Males"),
x_variable_name = "Satisfaction with life",
y_variable_name = "Body satisfaction",
grouping_variable_name = "Gender",
conf_level = myconf_level
)
)
mysp <- as.list(
as.data.frame(
statpsych::ci.cor2(
alpha = 1 - myconf_level,
cor1 = myr,
cor2 = myr2,
n1 = myn,
n2 = myn + 5
)
)
)
testthat::expect_equal(estimate$es_r_difference$effect_size[[3]], mysp$Estimate)
testthat::expect_equal(estimate$es_r_difference$LL[[3]], mysp$LL)
testthat::expect_equal(estimate$es_r_difference$UL[[3]], mysp$UL)
}
}
}
}
testthat::expect_snapshot(estimate)
})
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