Check nuisance regressors for rank and column problems

Inspects a block-wise nuisance regressor list before it is added to a baseline model. The check is run per block and compares nuisance columns against the baseline terms that would be constructed from basis, degree, and intercept.

Usage

check_nuisance(
  nuisance_list,
  sframe,
  basis = c("constant", "poly", "bs", "ns"),
  degree = 1,
  intercept = c("runwise", "global", "none"),
  tol = sqrt(.Machine$double.eps),
  duplicate_threshold = 1 - sqrt(.Machine$double.eps),
  na_action = c("drop", "zero", "median")
)

Arguments

nuisance_list

A list of numeric matrices or data frames, one per block.

sframe

A sampling frame.

basis, degree, intercept

Baseline model settings used to construct the comparison baseline terms.

tol

Numeric tolerance passed to QR rank checks.

duplicate_threshold

Absolute correlation threshold used to flag duplicate or near-duplicate columns.

na_action

Character; how to handle NA values in nuisance_list columns before the diagnostics run. "drop" (default) leaves NAs in place so any column containing one is treated as non-finite. "zero" replaces NA with 0 (matching the fMRIPrep leading-row convention) and "median" replaces NA with the column median; both repair an isolated leading NA (e.g. in DVARS or framewise displacement) so the regressor is retained. NaN and Inf are never repaired and remain non-finite.

Value

A nuisance_check object with ok, problems, by_block, and normalized nuisance_list elements.