Permutation-test summary from an opls_perm out_df table

Takes the out_df you showed (perm rows + one "non-permuted" row) and returns observed values, permutation distributions, and permutation p-values.

Usage

.perm_test_from_table(
  out_df,
  observed_label = "non-permuted",
  alternative = c("greater", "less"),
  add_one = TRUE,
  na_rm = TRUE
)

Arguments

out_df

data.frame with columns like q2_comp, r2_comp, aucs_te, aucs_tr, model (with one row "non-permuted"), and optionally r/r_abs.

observed_label

character. Label used in model for the observed row.

alternative

character. "greater" (default) tests obs > perm; "less" tests obs < perm.

add_one

logical. If TRUE, uses (1 + count)/(B + 1) p-value correction.

na_rm

logical. Drop NA values before computing p-values.

Value

A list with:

• observed: named numeric vector of observed metrics

• perm: list of numeric vectors for each metric

• p_value: named numeric vector of permutation p-values

• B: number of permutations used