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A new approach to selection and weighting of items in evaluative composite measurement scales
Author(s) -
Coste Joël,
Walter Eric,
Venot Alain
Publication year - 1995
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780142306
Subject(s) - weighting , ordinal scale , level of measurement , ordinal data , scale (ratio) , selection (genetic algorithm) , set (abstract data type) , measure (data warehouse) , computer science , gold standard (test) , interval (graph theory) , statistics , psychology , data mining , artificial intelligence , mathematics , machine learning , medicine , physics , quantum mechanics , combinatorics , radiology , programming language
Evaluative composite measurement scales (CMS) are increasingly used in medicine to measure complex constructs in the absence of a reference criterion or ‘gold standard’. However, the level of measurement provided by these instruments has usually been given little attention. This paper explores the influence of the characteristics of the item set and weighting on the level of measurment of an evaluative CMS. The approach is illustrated with an application to the scoring system of the Nottingham Health Profile. Simulations are provided to indicate when the composite score of item responses, on an ordinal or pass—fail scale, could be considered to achieve the properties of an interval scale.