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2 results

  • A Loss Function for Alpha Factor Analysis

  • Gerhard Derflinger
  • Journal:
    Psychometrika / Volume 49 / Issue 3 / September 1984
    Published online by Cambridge University Press:
    01 January 2025, pp. 325-330

  • Most of the factor solutions can be got by minimizing a corresponding loss function. However, up to now, a loss function for the alpha factor analysis (AFA) has not been known. The present paper establishes such a loss function for the AFA. Some analogies to the maximum likelihood factor analysis are discussed.

  • Simultaneous Optimization of Factor Assessibility and Representativeness: An Old Solution to a New Problem

  • Vernon L. Greene
  • Journal:
    Psychometrika / Volume 43 / Issue 2 / June 1978
    Published online by Cambridge University Press:
    01 January 2025, pp. 273-275

  • P. M. Bentler has shown that Rao's canonical factor analysis is in effect a psychometric analysis, leading to factors that are maximally assessible from the data. He contrasts this with Kaiser and Caffrey's alpha factor analysis that leads to factors that maximally represent the true factors in the content domain. Noting the problems associated with factors that may be highly assessible, but not very representative, or vice versa, Bentler suggests the need for a technique that would, insofar as possible, be optimal with respect to both criteria. Such a technique is presented here, and is shown to resolve into a traditional scaling method, which in turn acquires a richer psychometric interpretation.