Register a norms-based standardization version — register_norms

Creates a norms_version object and registers it in the .std_versions registry via .register_std_version().

Usage

register_norms_version(
  scores,
  version,
  lookup_table,
  raw_scores_fn = function(x) x,
  covar_fns,
  post_proc_fn = function(x) x,
  overwrite = FALSE,
  description = ""
)

Arguments

scores: A npsych_scores object, such as MOCATOTS(). Used to determine the scores class for registration.
version: Character string identifying this version (e.g., "nacc", "updated").
lookup_table: A data frame containing columns m (mean) and sd (standard deviation), plus covariate columns.
raw_scores_fn: An optional function that is applied to the raw scores before standardization. Example: the model fitted to get the updated_2025.06 regression coefficients for TRAILA was fitted to the negative TRAILA values to ensure higher values are better. Therefore raw_scores_fn = \(x) -x for this version.
covar_fns: A named list of functions. Names must match the non-statistic columns in lookup_table.
post_proc_fn: An option post processing function that is applied to standardized scores after the fact. For example, for norms based standardization of TRAILA, the sign of the z-scores are flipped to that larger z-scores are correlated with better performance. Hence, post_proc_fn = \(x) -x.
overwrite: Logical. If FALSE (the default), an error is thrown if a version with the same version and scores class already exists in the registry. If TRUE, the existing version is overwritten with the new one.
description: An optional single string describing the version.

Value

Invisible NULL. Called for its side effect of registering the version in the internal .std_versions registry.