Nothing
set.seed(1)
df <- data.frame(
ARM = with_label(rep("A: Drug X", 162), "Arm"),
AVAL = runif(162, 0, 100),
AVALCAT1 = as.factor(sample(c(1, "BLQ"), 162, replace = TRUE)),
VISIT = with_label(as.factor(rep(c(rep("Day 1", 5), rep("Day 2", 4)), 18)), "Visit"),
NFRLT = with_label(as.factor(rep(c(0, seq(0, 42, 6)), 18)), "Nominal Time")
)
testthat::test_that("imputation_rule works correctly for 1/3 imputation rule", {
x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
result <- imputation_rule(df, x_stats, "max", "1/3")
res <- testthat::expect_snapshot(result)
x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
result <- imputation_rule(df, x_stats, "mean", "1/3")
res <- testthat::expect_snapshot(result)
x_stats <- s_summary(df$AVAL[df$NFRLT == 6])
result <- imputation_rule(df, x_stats, "geom_mean", "1/3", post = TRUE)
res <- testthat::expect_snapshot(result)
x_stats <- s_summary(df$AVAL[df$NFRLT == 18])
result <- imputation_rule(df, x_stats, "max", "1/3", post = TRUE)
res <- testthat::expect_snapshot(result)
})
testthat::test_that("imputation_rule works correctly for 1/2 imputation rule", {
x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
result <- imputation_rule(df, x_stats, "max", "1/2")
res <- testthat::expect_snapshot(result)
x_stats <- s_summary(df$AVAL[df$NFRLT == 0])
result <- imputation_rule(df, x_stats, "mean", "1/2")
res <- testthat::expect_snapshot(result)
x_stats <- s_summary(df$AVAL[df$NFRLT == 6])
result <- imputation_rule(df, x_stats, "geom_mean", "1/2", post = TRUE)
res <- testthat::expect_snapshot(result)
x_stats <- s_summary(df$AVAL[df$NFRLT == 18])
result <- imputation_rule(df, x_stats, "max", "1/2", post = TRUE)
res <- testthat::expect_snapshot(result)
})
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