Premium
Methodological and statistical problems in the construction of composite measurement scales: A survey of six medical and epidemiological journals
Author(s) -
Coste Joël,
Fermanian Jacques,
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.4780140402
Subject(s) - overfitting , reliability (semiconductor) , computer science , multivariate statistics , construct (python library) , relevance (law) , construct validity , epidemiology , quality (philosophy) , data science , statistics , econometrics , psychometrics , medicine , mathematics , pathology , machine learning , power (physics) , physics , philosophy , epistemology , quantum mechanics , artificial neural network , political science , law , programming language
Composite measurement scales (CMS) are increasingly used in medicine to measure complex phenomena or concepts such as disease risk and severity, physical and psychological functioning and quality of life. To investigate the methodology currently used in the construction of CMS, we examined 46 studies recently published in six major medical and epidemiological journals. Important measurement properties such as measurement level, content and construct validity and reliability are often neglected. Statistical methods, particularly multivariate methods are frequently misused; verifications of model relevance and assumptions, and cross‐validations to avoid overfitting are seldom performed. We propose recommendations for the construction and the presentation of CMS, to help authors and investigators to report and choose, respectively, measurement instruments for a complex phenomenon.