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A Beginner's Guide to Factor Analysis: Focusing on Exploratory Factor Analysis [PDF]
Tutorials in Quantitative Methods for Psychology, 2013 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.
An Gie Yong, Sean Pearce
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Best Practices for Your Exploratory Factor Analysis: A Factor Tutorial
RAC: Revista de Administração Contemporânea, 2021 Context: exploratory factor analysis (EFA) is one of the statistical methods most widely used in administration; however, its current practice coexists with rules of thumb and heuristics given half a century ago. Objective: the purpose of this article is
Pablo Rogers
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Evaluating the use of exploratory factor analysis in psychological research. [PDF]
, 1999 Despite the widespread use of exploratory factor analysis in psychological research, researchers often make questionable decisions when conducting these analyses.
Leandre R. Fabrigar +3 more
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Bayesian Exploratory Factor Analysis [PDF]
Journal of Econometrics, 2014 This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings.
Gabriella Conti +3 more
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Sparse Exploratory Factor Analysis [PDF]
Psychometrika, 2017 Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could ...
Nickolay T. Trendafilov +2 more
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Exploratory factor analysis for small samples [PDF]
Behavior Research Methods, 2011 Traditionally, two distinct approaches have been employed for exploratory factor analysis: maximum likelihood factor analysis and principal component analysis. A third alternative, called regularized exploratory factor analysis, was introduced recently in the psychometric literature.
Sunho Jung, Soonmook Lee
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Caspian Journal of Health Research, 2016 Objectives: Protecting children from abuse is a public responsibility. Having a valid tool to assess child abuse is necessary. Methods: The present analysis variance–covariance matrix study recruited 360 elementary school students ...
Hashem Mohammadian +2 more
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Exploratory factor analysis with structured residuals for brain network data
Network Neuroscience, 2021 Dimension reduction is widely used and often necessary to make network analyses and their interpretation tractable by reducing high-dimensional data to a small number of underlying variables.
Erik-Jan van Kesteren, Rogier A. Kievit
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The SAGE Encyclopedia of Research Design, 2022 Selection of factors to be extracted: Theory is the first criteria to determine the number of factors to be extracted. From theory, we know that the number of factors extracted does make sense.
Shane T. Mueller
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Engineering Management in Production and Services, 2021 Factor analysis is a standard statistical technique for reducing data dimensionality, which is widely used in sociology, psychology, and demography. Also, financial and insurance institutions commonly use such a technique for marketing research.
Jurczak Jolanta, Jurczak Grzegorz
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