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Handbook of Multivariate Experimental Psychology pp 289–316Cite as

Multimode Factor Analysis

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Part of the book series: Perspectives on Individual Differences ((PIDF))

Abstract

If a number of persons are measured on a number of variables (tests), the data design can be represented by a (two-way classified) matrix of persons by variables. These identifying classifications, reflecting independently defined sets of entities, have been termed observational “modes” or “modes of classification” (Tucker, 1966a). Each entry in the two-mode matrix provides information about the relation between the person and the variable and is designated by the Cartesian product of the sets of classification indices. As additional independent sets of entities are included in the design, for example, situations, conditions, or occasions, the number of modes increases, yielding a multimode design.

Chapter written while the author was serving as Technical Specialist with the Fourth World Bank Education Project, Ministry of Education, Monrovia, Liberia, West Africa, under contract with the Institute for International Research (IIR), McLean, Virginia, USA. This chapter is dedicated to Andrew R. Baggaley, mentor and friend.

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Authors and Affiliations

  1. Department of Psychology, University of Queensland, St. Lucia, Queensland, Australia

    Conrad Wesley Snyder Jr.

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  1. Conrad Wesley Snyder Jr.
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Editors and Affiliations

  1. Pennsylvania State University, University Park, Pennsylvania, USA

    John R. Nesselroade

  2. University of Hawaii at Manoa, 96844, Honolulu, Hawaii, USA

    Raymond B. Cattell

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Snyder, C.W. (1988). Multimode Factor Analysis. In: Nesselroade, J.R., Cattell, R.B. (eds) Handbook of Multivariate Experimental Psychology. Perspectives on Individual Differences. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0893-5_8

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  • DOI: https://doi.org/10.1007/978-1-4613-0893-5_8

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