Identifying the best common factor model via exploratory eactor analysis  

作　　者：HE Bao-hua TANG Rui TAGN Qi-yi 

机构地区：[1]School of Big Data,Fuzhou University of International Studies and Trade,Fuzhou 350202,China [2]School of Mathematics,Sun Yat-Sen University,Guangzhou 510275,China [3]Department of Computer Science,University of Bath,UK [4]Institute of Insect Science,Zhejiang University,Hangzhou 310058,China.

出　　处：《Applied Mathematics(A Journal of Chinese Universities)》2024年第1期24-33,共10页高校应用数学学报（英文版）（B辑）

基　　金：Supported by the National Basic Research Program of China(2010CB126200);the National Natural Science Foundation of China(30370914)。

摘　　要：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.

关 键 词：factor analysis Shapiro-Wilk NORMALITY RESIDUALS 

分 类 号：O212.1[理学—概率论与数理统计]