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High-dimensional Full-information Item Factor Analysis

  • R. Darrell Bock
  • Steven Schilling
Part of the Lecture Notes in Statistics book series (LNS, volume 120)

Abstract

Item factor analysis is unexcelled as a technique of exploration and discovery in the study of behavior. From binary-scored responses to a multiple-item test or scale, it determines the dimensionality of individual variation among the respondents and reveals attributes of the items defining each dimension. In practical test construction and scoring, it is the best guide to item selection and revision, as well as an essential preliminary step in justifying unidimensional IRT item analysis. Because hundreds of items may be analyzed jointly, the detail and generality that may be achieved exceeds that of any other procedure for exploring relationships among responses.

Keywords

Marginal Probability Item Parameter Quadrature Point Hadamard Matrix Likelihood Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1997

Authors and Affiliations

  • R. Darrell Bock
    • 1
  • Steven Schilling
    • 1
  1. 1.University of ChicagoUSA

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