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exploratory factor analysis (understanding statistics)

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What this book knows

Exploratory factor analysis reveals hidden structure in data by identifying the fewest latent constructs that explain observed correlations among measured variables.

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mind-and-cognitioneducation-and-formation

mind-and-cognition

Factor analysis refers to a set of statistical procedures designed to determine the number of distinct constructs needed to account for the pattern of correlations among a set of measures.
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The common factor model is based on more realistic assumptions because it directly acknowledges the existence of unique variance.
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The purpose of oblique rotation is to arrive at a solution with simple structure that takes into account correlations among factors and estimates the unique effects of each common factor.
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education-and-formation

Researchers should carefully consider assumptions prior to collecting data; a researcher's choices in variable selection can have a major impact on whether assumptions are satisfied.
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EFA was developed more than 100 years ago and has been extensively applied in many scientific disciplines, yet EFA is a complex statistic.
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PCA is the default extraction method, making it easy for inexperienced researchers to apply an inappropriate extraction method.
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