A Beginner's Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

By An Gie Yong, S. Pearce. 2013

3,143 citations recorded by the source corpus.

The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.

Subfields: Computer Networks and Communications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/24e784058b56c4de64f247dec89fb7a759efa116

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. S. Buckley
2. Bertha Joseph Ngereja
3. Mark D'Esposito
4. Justin Riddle
5. B. Andersen
6. Abhinava Barthakur
7. J. Piet Hausberg
8. Bassam Hussein

In Management Science and Operations Research

1. Bertha Joseph Ngereja
2. Justin Riddle
3. B. Andersen
4. J. Piet Hausberg
5. Bassam Hussein
6. Krystallia Moysidou

Citations in the corpus

• In crowdfunding we trust: A trust-building model in lending crowdfunding (2020, methodology): “Moreover, the Kaiser-MeyerOlkin (KMO) value was 0.794, exceeding the recommended value of 0.6 and Bartlett’s test of sphericity reached statistical significance (chi-square = 2360.53, df = 253), together indicating that we had distinct and reliable factors indeed (Yong & Pearce, 2013).”
• Does Project-Based Learning (PBL) Promote Student Learning? A Performance Evaluation (2020, methodology): “The reason for the close examination was partly due to the nature of the questions, most of which were designed as statements of individual perceptions, and partly due to the number of participants (n < 300), which meant that validating them using methods such as factor analysis would not have been ”
• The impact of mathematics anxiety on self-regulated learning and mathematical literacy (2020, background): “Also, the standardised factor loadings are higher than 0.5, suggesting that the observed variables are closely related to their associated factors (Yong & Pearce, 2013).”
• A guide for concurrent TMS-fMRI to investigate functional brain networks (2022, methodology): “The threshold of 10% was selected based on thresholding convention from other techniques, such as factor analysis (Yong and Pearce, 2013), and the use of a lower threshold would require more manual inspection.”
• Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness (2022, background): “33) serves as an a priori threshold for including the subscale in the symptom composite.(28) If a subscale shows a significant loading for multiple dimensions, then we recommend exclusion as the subscale likely conflates the dimensions of interest.”