The x_by_b implementation tests whether treatment effects differ
across k >= 2 related conditions measured on the same block (e.g.
repeated measures on the same subject, or a randomized block design).
It accepts a continuous response, a treatment/grouping variable, and a
blocking variable via x_by_b().
Arguments
friedman_def_xby's baseline fn takes no arguments beyond .proc —
nothing is currently passed through ... in FRIEDMAN_TEST() or
statim::via().
Variants
None. friedman_def_xby declares only a base baseline in its
statim::agendas() — no variant() entries.
Grouped Friedman default class
By default, returns a class_friedman_test object. There is only one
base baseline — no variants — so there's nothing else to inherit or
override.
Examples
set.seed(123)
x = rnorm(30)
g = rep(letters[1:3], 10)
b = rep(1:10, each = 3)
FRIEDMAN_TEST(x_by_b(x, g, b))
#> -- Summary ---------------------------------------------------------------------
#>
#> ──────────────────────────
#> statistic df p_value
#> ──────────────────────────
#> 1.400 2 0.497
#> ──────────────────────────
#>
#>