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Nonlinear factors in two dimensions

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Abstract

Intercorrelations among tests nonlinearly related to underlying dimensions require more linear factors than content would demand. For the case of two independent underlying content dimensions, a fictitious example is constructed and made to yield a transformation useful for the nonlinear analysis of certain empirical data. That transformation, when applied to a standard factorization (centroid or principal components if certain symmetries obtain) of the appropriate empirical correlations, yields parameters descriptive of plausible nonplanar regression surfaces for tests on the two underlying dimensions. An empirical example is presented and discussed.

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  1. Department of the Army, Personnel Research Branch, Tago, USA

    W. A. Gibson

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  1. W. A. Gibson
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The opinions expressed are those of the author and are not to be construed as reflecting official Department of the Army policy.

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Gibson, W.A. Nonlinear factors in two dimensions. Psychometrika 25, 381–392 (1960). https://doi.org/10.1007/BF02289755

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  • DOI: https://doi.org/10.1007/BF02289755

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