Identifying the best common factor model via exploratory eactor analysis

Bao Hua He; Rui Tang; Qi Yi Tagn

doi:10.1007/s11766-024-3544-7

Identifying the best common factor model via exploratory eactor analysis

Bao Hua He, Rui Tang, Qi Yi Tagn

Department of Computer Science

Research output: Contribution to journal › Article › peer-review

1 Citation (SciVal)

Abstract

Currently, there is no solid criterion for judging the quality of the estimators in factor analysis. This paper presents a new evaluation method for exploratory factor analysis that pinpoints an appropriate number of factors along with the best method for factor extraction. The proposed technique consists of two steps: testing the normality of the residuals from the fitted model via the Shapiro-Wilk test and using an empirical quantified index to judge the quality of the factor model. Examples are presented to demonstrate how the method is implemented and to verify its effectiveness.

Original language	English
Pages (from-to)	24-33
Number of pages	10
Journal	Applied Mathematics
Volume	39
Issue number	1
Early online date	8 Mar 2024
DOIs	https://doi.org/10.1007/s11766-024-3544-7
Publication status	Published - 31 Mar 2024

Funding

Supported by the National Basic Research Program of China(2010CB126200) and the National Natural Science Foundation of China(30370914).

Funders	Funder number
National Natural Science Foundation of China	30370914
National Key Research and Development Program of China	2010CB126200

Keywords

62H25
factor analysis
normality
residuals
Shapiro-Wilk

ASJC Scopus subject areas

Applied Mathematics

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10.1007/s11766-024-3544-7

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AB - Currently, there is no solid criterion for judging the quality of the estimators in factor analysis. This paper presents a new evaluation method for exploratory factor analysis that pinpoints an appropriate number of factors along with the best method for factor extraction. The proposed technique consists of two steps: testing the normality of the residuals from the fitted model via the Shapiro-Wilk test and using an empirical quantified index to judge the quality of the factor model. Examples are presented to demonstrate how the method is implemented and to verify its effectiveness.

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KW - factor analysis

KW - normality

KW - residuals

KW - Shapiro-Wilk

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Identifying the best common factor model via exploratory eactor analysis

Abstract

Funding

Keywords

ASJC Scopus subject areas

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