Nothing
library(testthat)
library(Causata)
equals <- testthat::equals
context("GetStratifiedSample")
test_that("basic sampling probabilities are correct with more negative", {
df <- data.frame(iv=rnorm(10), dv=c(0, 1, 0, 1, 1, 1, 0, 0, 0, 0))
sample.probabilities <- Causata:::SamplingProbabilities(df$dv, 0)
expect_that(length(sample.probabilities), equals(2))
expect_that(sample.probabilities$A, equals(0.8164966, tolerance=0.000001))
expect_that(sample.probabilities$B, equals(1))
}
)
test_that("basic sampling probabilities are correct with more positive", {
df <- data.frame(iv=rnorm(10), dv=c(1, 1, 0, 1, 1, 0, 1, 0,1, 1))
sample.probabilities <- Causata:::SamplingProbabilities(df$dv, 0)
expect_that(length(sample.probabilities), equals(2))
expect_that(sample.probabilities$A, equals(1))
expect_that(sample.probabilities$B, equals(0.6546537, tolerance=0.000001))
}
)
test_that("sampling where stratification.variable is single-valued and negative", {
df <- data.frame(iv=rnorm(10), dv=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0))
sample.probabilities <- Causata:::SamplingProbabilities(df$dv, 0)
expect_that(length(sample.probabilities), equals(2))
expect_that(sample.probabilities$A, equals(0.3162278, tolerance=0.000001))
expect_that(sample.probabilities$B, equals(1))
}
)
test_that("sampling where stratification.variable is single-valued and positive", {
df <- data.frame(iv=rnorm(10), dv=c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1))
sample.probabilities <- Causata:::SamplingProbabilities(df$dv, 0)
expect_that(length(sample.probabilities), equals(2))
expect_that(sample.probabilities$A, equals(1))
expect_that(sample.probabilities$B, equals(0.3162278, tolerance=0.000001))
}
)
test_that("stratification value", {
df <- data.frame(iv=rnorm(10), dv=c(0, 1, 0, 3, 1, 1, 0, 0, 0, 3))
sample.probabilities <- Causata:::SamplingProbabilities(df$dv, stratification.value=3)
expect_that(length(sample.probabilities), equals(2))
expect_that(sample.probabilities$A, equals(1))
expect_that(sample.probabilities$B, equals(0.5))
}
)
test_that("stratification value is floating point", {
df <- data.frame(iv=rnorm(10), dv=c(0, 0.012, 0, 0.234324, 134.34, 13.4, 0, 0, 0, 0))
sample.probabilities <- Causata:::SamplingProbabilities(df$dv, 0)
expect_that(length(sample.probabilities), equals(2))
expect_that(sample.probabilities$A, equals(0.8164966, tolerance=0.000001))
expect_that(sample.probabilities$B, equals(1))
}
)
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