Factor analysis of Likert scale: Analysis and Interpretation using SPSS

Опубликовано: 25 Январь 2024
на канале: Mohamed Benhima

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This tutorial explains how to perform and interpret exploratory factor analysis (EFA) on Likert scale in SPSS. I discuss how to enter the data, select the various options, interpret the output (e.g., communalities, eigenvalues, factor loadings). I also discuss the difference among extraction techniques (Principal components analysis or PCA, Principal Axis Factoring or PAF and Maximum Likelihood or ML). I also discuss the difference between orthogonal and oblique rotation techniques like Varimax and Promax within SPSS. Likert scale is a commonly used rating scale in surveys, typically containing several statements, and respondents rate their level of agreement or disagreement on a scale ranging from strongly disagree coded as 1 to strongly agree coded as 5.
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Guidelines and dataset: https://drive.google.com/drive/folder...
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📌 Mohamed Benhima, PhD
WhatsApp: +212619398603 / wa.link/l6jvny
LinkedIn: / mohamed-benhima-phd-6a1087109
Mohammed V University, Rabat, Morocco ( [email protected] )
Sorbonne University, Paris, France ( [email protected] )