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In the context of factor analysis, factor loadings are numerical values that demonstrate how individual variables cluster onto underlying dimensions. In a factor analysis summary table, higher factor loadings indicate a stronger association between a variable and a specific factor, and researchers typically rely on the highest factor loadings to interpret and define each resulting construct.

Factor Loadings

In an empirical study of music preferences, researchers Peter Rentfrow and Samuel Gosling had over $$1,700$$ university students rate their liking for $$14$$ different popular music genres. By submitting these variables to a factor analysis, they identified four distinct clusters. To demonstrate this, they organized the results in a table of factor loadings, where the numerical values showed the strength of each genre's correlation with the factors. Based on the highest factor loadings, the researchers interpreted and labeled the four underlying constructs: Reflective and Complex (e.g., highly loaded by blues and jazz), Intense and Rebellious (e.g., rock, heavy metal), Upbeat and Conventional (e.g., country, pop), and Energetic and Rhythmic (e.g., rap/hip-hop, electronica).

Example of Factor Analysis: Music Preferences

In the context of factor analysis, the numerical values that demonstrate how individual variables cluster onto underlying dimensions are called factor ______.

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