A Modernized Heuristic Approach to Robust Exploratory Factor Analysis

被引：8

作者：

Gibson, Terry O., Jr. ^{[1
]}

Morrow, Jennifer Ann ^{[2
]}

Rocconi, Louis M. ^{[2
]}

机构：

[1] Pellissippi State Community Coll, Knoxville, TN 37932 USA

[2] Univ Tennessee, Knoxville, TN 37996 USA

来源：

QUANTITATIVE METHODS FOR PSYCHOLOGY | 2020年 / 16卷 / 04期

关键词：

Robust EFA; Polychoric; Modern EFA; Schwarz's BIC; SAMPLE-SIZE; VARIABLES; PROGRAM;

D O I：

10.20982/tqmp.16.4.p295

中图分类号：

C [社会科学总论];

学科分类号：

03 ; 0303 ;

摘要：

Exploratory Factor Analysis (EFA) is a widely used approach for exploring latent traits. The EFA literature contains many inconsistencies regarding appropriate sample sizes, remedies for violation of assumptions, and the use of rotational methods. Given that EFA is an iterative process, which involves varied decision-making, the objective of the current paper is to highlight the use of modernized methods using a heuristic approach for performing robust EFA to achieve optimal results. An example implementing these methods is presented using free online software (FACTOR). The paper concludes with seven recommendations for achieving well-defined factor solutions.

引用

页码：295 / 307

页数：13

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