RatingScaleReduction package: stepwise rating scale item reduction without predictability loss

TL;DR

This paper introduces the RatingScaleReduction package that employs an AUC ROC-based stepwise method to reduce rating scale items efficiently without sacrificing predictive accuracy.

Contribution

It presents a novel stepwise reduction method using AUC ROC, implemented in an R package, for maintaining predictability while decreasing rating scale items.

Findings

Effective reduction of rating scale items demonstrated in multiple case studies

Maintains predictability despite item reduction

Provides an accessible R package for practical use

Abstract

This study presents an innovative method for reducing the number of rating scale items without predictability loss. The "area under the re- ceiver operator curve method" (AUC ROC) is used to implement in the RatingScaleReduction package posted on CRAN. Several cases have been used to illustrate how the stepwise method has reduced the number of rating scale items (variables).