Nothing
test_that("Compare estimate_proportion to ESCI_One_Proportion example", {
statpsych_version <- as.numeric(gsub("\\.", "", utils::packageVersion("statpsych")))
estimate <- esci::estimate_proportion(
cases = c(8, 22-8),
outcome_variable_levels = c("Affected", "Not Affected")
)
testthat::expect_s3_class(estimate, "esci_estimate")
if (statpsych_version > 150) {
mysp <- as.list(
as.data.frame(
statpsych::ci.prop(.05, 8, 22)
)[1, ]
)
} else {
mysp <- as.list(
as.data.frame(
statpsych::ci.prop1(.05, 8, 22)
)[1, ]
)
}
testthat::expect_s3_class(estimate, "esci_estimate")
testthat::expect_snapshot(estimate)
testthat::expect_equal(estimate$es_proportion$effect_size, .3636363636)
# Can't compare the CI to esci because statpsych uses a slight adjustment
# in its calculation of the CI
testthat::expect_equal(estimate$es_proportion$LL, mysp$LL)
testthat::expect_equal(estimate$es_proportion$UL, mysp$UL)
myplot <- plot_proportion(estimate)
testthat::expect_s3_class(myplot, "ggplot")
})
test_that("Call estimate_proportion with vector", {
statpsych_version <- as.numeric(gsub("\\.", "", utils::packageVersion("statpsych")))
dep_status <- as.factor(
c(
rep("Depressed", 8),
rep("NotDepressed", 22-8),
NA,
NA,
NA
)
)
myconf_level <- 0.95
myconf_levels <- c(0.90, 0.95, 0.99)
for (myconf_level in myconf_levels) {
estimate <- estimate_proportion(
outcome_variable = dep_status,
count_NA = FALSE,
conf_level = myconf_level
)
if (statpsych_version > 150) {
mysp <- as.list(
as.data.frame(
statpsych::ci.prop(1 - myconf_level, 8, 22)
)[1, ]
)
} else {
mysp <- as.list(
as.data.frame(
statpsych::ci.prop1(1 - myconf_level, 8, 22)
)[1, ]
)
}
testthat::expect_s3_class(estimate, "esci_estimate")
testthat::expect_equal(estimate$es_proportion$effect_size, .3636363636)
# Can't compare the CI to esci because statpsych uses a slight adjustment
# in its calculation of the CI
testthat::expect_equal(estimate$es_proportion$LL, mysp$LL)
testthat::expect_equal(estimate$es_proportion$UL, mysp$UL)
}
testthat::expect_snapshot(estimate)
myplot <- plot_proportion(estimate)
testthat::expect_s3_class(myplot, "ggplot")
})
test_that("Call estimate_proportion with dataframe", {
statpsych_version <- as.numeric(gsub("\\.", "", utils::packageVersion("statpsych")))
dep_status <- as.factor(
c(
rep("Depressed", 8),
rep("NotDepressed", 22-8),
NA,
NA,
NA
)
)
dep_data <- data.frame(
depression_status = dep_status,
other = as.factor(c(rep("G1", 12), rep("G2", 13)))
)
myconf_level <- 0.95
myconf_levels <- c(0.90, 0.95, 0.99)
for (myconf_level in myconf_levels) {
estimate <- estimate_proportion(
dep_data,
depression_status,
count_NA = FALSE,
conf_level = myconf_level
)
if (statpsych_version > 150) {
mysp <- as.list(
as.data.frame(
statpsych::ci.prop(1 - myconf_level, 8, 22)
)[1, ]
)
} else {
mysp <- as.list(
as.data.frame(
statpsych::ci.prop1(1 - myconf_level, 8, 22)
)[1, ]
)
}
testthat::expect_s3_class(estimate, "esci_estimate")
testthat::expect_equal(estimate$es_proportion$effect_size, .3636363636)
# Can't compare the CI to esci because statpsych uses a slight adjustment
# in its calculation of the CI
testthat::expect_equal(estimate$es_proportion$LL, mysp$LL)
testthat::expect_equal(estimate$es_proportion$UL, mysp$UL)
}
testthat::expect_snapshot(estimate)
myplot <- plot_proportion(estimate)
testthat::expect_s3_class(myplot, "ggplot")
})
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