Register a regression-based standardization version — register_regression

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

Usage

register_regression_version(
  scores,
  version,
  coefs,
  raw_scores_fn = function(x) x,
  covar_fns = NULL,
  post_proc_fn = function(x) x,
  description = "",
  overwrite = FALSE
)

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").
coefs: A named numeric vector of regression coefficients. Must include "intercept" and "rmse" entries.
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.
description: An optional single string describing the version.
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.

Value

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