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The eigenvalue is a measure of how much of the variance of the observed variables a...

The eigenvalue is a measure of how much of the variance of the observed variables a factor explains. Any factor with an eigenvalue ≥1 explains more variance than a single observed variable, so if the factor for socioeconomic status had an eigenvalue of 2.3 it would explain as much variance as 2.3 of the three variables. This factor, which captures most of the variance in those three variables, could then be used in another analysis. The factors that explain the least amount of variance are generally discarded. How do we determine how many factors are useful to retain?

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