Author, as appears in the article.: Lorenzo-Seva, Urbano; Ferrando, Pere J.;

Department: Psicologia

URV's Author/s: Ferrando Piera, Pere Joan / Lorenzo Seva, Urbano

Keywords: Smoothing method Robust estimation Polychoric correlation Not positive definite Heywood cases

Abstract: 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.

Thematic Areas: 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

licence for use: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 1070-5511

Author's mail: perejoan.ferrando@urv.cat urbano.lorenzo@urv.cat

Author identifier: 0000-0002-3133-5466 0000-0001-5369-3099

Record's date: 2023-02-19

Papper version: info:eu-repo/semantics/publishedVersion

Link to the original source: https://www.tandfonline.com/doi/full/10.1080/10705511.2020.1735393

Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/

Papper original source: Structural Equation Modeling-A Multidisciplinary Journal. 28 (1): 138-147

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

Article's DOI: 10.1080/10705511.2020.1735393

Entity: Universitat Rovira i Virgili

Journal publication year: 2021

Publication Type: Journal Publications