Norms-Based Standardization Version

Create a norms_version object that stores a lookup table and covariate functions for norms-based standardization. Inherits from std_version.

Usage

norms_version(
  scores_class,
  version_id,
  lookup_table,
  covar_fns,
  raw_scores_fn = function(x) x,
  post_proc_fn = function(x) x,
  description = ""
)

Arguments

scores_class

A single non-empty string giving the npsych_scores subclass this version applies to (e.g., "MOCATOTS").

version_id

A single non-empty string uniquely identifying this version within its method and scores class.

lookup_table

A data frame containing columns m (mean) and sd (standard deviation), plus covariate columns.

covar_fns

A named list of functions. Names must match the non-statistic columns in lookup_table.

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.

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.

Value

An S7 object of class norms_version with properties inherited from std_version plus lookup_table and covar_fns.