Single T-Test, Tidied — single_t

Runs a t-test comparing .var between the two levels of .class, tidied into one row with group sizes/SDs and fold-change added.

Usage

single_t_test(
  .data,
  .var,
  .class,
  .id = NULL,
  alternative = "two.sided",
  conf.level = 0.95,
  paired = FALSE,
  ...
)

Arguments

.data: A data frame or tibble.
.var: Name (string) of the continuous column to test.
.class: Name (string) of a binary (2-level) classification column.
.id: Name (string, optional) of a subject/record identifier column. When paired = TRUE, pass this to pair observations by matching .id across the two groups rather than by row position — every id must have exactly one observation in each group. If paired = TRUE and .id is omitted, observations are paired by row order within each group, which silently produces meaningless results if the two groups aren't already sorted into corresponding order.
alternative: One of "two.sided" (default), "greater", or "less".
conf.level: Confidence level for the interval.
paired: Logical; paired t-test.
...: Additional arguments passed to t.test.

Value

A one-row tibble.

Examples

mtcars |>
  dplyr::mutate(am = factor(am)) |>
  single_t_test("mpg", "am")
#> # A tibble: 1 × 18
#>   estimate estimate1 estimate2 statistic p.value parameter conf.low conf.high
#>      <dbl>     <dbl>     <dbl>     <dbl>   <dbl>     <dbl>    <dbl>     <dbl>
#> 1    -7.24      17.1      24.4     -3.77 0.00137      18.3    -11.3     -3.21
#> # ℹ 10 more variables: method <chr>, alternative <chr>, var <chr>,
#> #   group1 <chr>, group2 <chr>, n_per_group <chr>, sd_per_group <chr>,
#> #   log_p <dbl>, fold_change <dbl>, log2_fold_change <dbl>