Why Factor Analysis Often is the Incorrect Model for Analyzing Bipolar Concepts, and What Model to Use Instead
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Why Factor Analysis Often is the Incorrect Model for Analyzing Bipolar Concepts, and What Model to Use Instead
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1994
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Abstract
Factor analysis of data that conform to the unfolding
model often results in an extra factor. This artificial
extra factor is particularly important when data that
conform to a bipolar unidimensional unfolding scale
are factor analyzed. One bipolar dimension is expected,
but two factors are found and often are interpreted
as two unrelated dimensions. Although this
extra factor phenomenon was pointed out in the early
1960s, it still is not widely recognized. The extra factor
phenomenon in the unidimensional case is reviewed
here. A numerical illustration is provided, and a number
of diagnostics that can be used to determine
whether data conform to the unidimensional unfolding
model better than to the factor model are discussed.
These diagnostics then are applied to an empirical
example. Index terms: factor analysis, factor interpretation
problems, rating scales, unfolding diagnostics,
unfolding model.
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Van Schuur, Wijbrandt H.; Kiers, Henk A.. (1994). Why Factor Analysis Often is the Incorrect Model for Analyzing Bipolar Concepts, and What Model to Use Instead. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/120012.
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