ard_stats_t_test: ARD t-test

In cardx: Extra Analysis Results Data Utilities

ARD t-test

Description

Analysis results data for paired and non-paired t-tests.

Usage

ard_stats_t_test(data, variables, by = NULL, conf.level = 0.95, ...)

ard_stats_paired_t_test(data, by, variables, id, conf.level = 0.95, ...)

Arguments

data	(data.frame) a data frame. See below for details.
variables	(tidy-select) column names to be compared. Independent t-tests will be computed for each variable.
by	(tidy-select) optional column name to compare by.
conf.level	(scalar numeric) confidence level for confidence interval. Default is 0.95.
...	arguments passed to t.test()
id	(tidy-select) column name of the subject or participant ID

Details

For the ard_stats_t_test() function, the data is expected to be one row per subject. The data is passed as t.test(data[[variable]] ~ data[[by]], paired = FALSE, ...).

For the ard_stats_paired_t_test() function, the data is expected to be one row per subject per by level. Before the t-test is calculated, the data are reshaped to a wide format to be one row per subject. The data are then passed as ⁠t.test(x = data_wide[[<by level 1>]], y = data_wide[[<by level 2>]], paired = TRUE, ...)⁠.

Value

ARD data frame

Examples

cards::ADSL |>
  dplyr::filter(ARM %in% c("Placebo", "Xanomeline High Dose")) |>
  ard_stats_t_test(by = ARM, variables = c(AGE, BMIBL))

# constructing a paired data set,
# where patients receive both treatments
cards::ADSL[c("ARM", "AGE")] |>
  dplyr::filter(ARM %in% c("Placebo", "Xanomeline High Dose")) |>
  dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>
  dplyr::arrange(USUBJID, ARM) |>
  ard_stats_paired_t_test(by = ARM, variables = AGE, id = USUBJID)

cardx documentation built on Sept. 11, 2024, 9:12 p.m.