Autor segons l'article: Lorenzo-Seva, Urbano; Ferrando, Pere J
Departament: Psicologia
Autor/s de la URV: Ferrando Piera, Pere Joan / Lorenzo Seva, Urbano
Paraules clau: Smoothing method Robust estimation Polychoric correlation Not positive definite Heywood cases
Resum: Least-squares exploratory factor analysis based on tetrachoric/polychoric correlations is a robust, defensible and widely used approach for performing item analysis, especially in the first stages of scale development. A relatively common problem in this scenario, however, is that the inter-item correlation matrix fails to be positive definite. This paper, which is largely intended for practitioners, aims to provide a didactic discussion about the causes, consequences and remedies of this problem. The discussion is more applied than statistical and based on the factor analysis model, and the problem is linked to that of improper solutions. Solutions for preventing the problem from occurring, and the smoothing corrections available at present are described and discussed. A new smoothing algorithm is also proposed.
Àrees temàtiques: Sociology and political science Sociologia i política Social sciences, mathematical methods Psychology Psicología Modeling and simulation Mathematics, interdisciplinary applications Matemática / probabilidade e estatística General o multidisciplinar General economics,econometrics and finance General decision sciences Economics, econometrics and finance (miscellaneous) Economics, econometrics and finance (all) Economia Decision sciences (miscellaneous) Decision sciences (all) Ciencias sociales
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 1070-5511
Adreça de correu electrònic de l'autor: urbano.lorenzo@urv.cat perejoan.ferrando@urv.cat
Identificador de l'autor: 0000-0001-5369-3099 0000-0002-3133-5466
Data d'alta del registre: 2024-10-12
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Structural Equation Modeling-A Multidisciplinary Journal. 28 (1): 138-147
Referència de l'ítem segons les normes APA: Lorenzo-Seva, Urbano; Ferrando, Pere J (2021). Not Positive Definite Correlation Matrices in Exploratory Item Factor Analysis: Causes, Consequences and a Proposed Solution. Structural Equation Modeling-A Multidisciplinary Journal, 28(1), 138-147. DOI: 10.1080/10705511.2020.1735393
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2021
Tipus de publicació: Journal Publications
Repositori URV