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Multivariate Analysis of Discrete Data

  • Chapter
Handbook of Multivariate Experimental Psychology

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

Abstract

Discrete rather than continuous variables are the norm in most datasets analyzed in the social and behavioral sciences. Many researchers routinely apply continuous-data models to analyze discrete data, but this practice is valid only in limited ways. Recent developments in statistical theory, computational algorithms, and social science methodology make it possible to analyze discrete data in a valid manner without recourse to models based on continuity (or normality) assumptions. This chapter presents an overview of one approach to the analysis of discrete data, that based on log-linear models. Log-linear models for discrete data are (1) just as flexible as corresponding linear models for continuous data, (2) consistent with distributional assumptions appropriate for discrete variables, and (3) based on measures of relationship (bivariate or multivariate) that are meaningful for discrete variables (odds, odds ratios, and their logarithms).

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Author information

Authors and Affiliations

  1. Departments of Sociology and Statistics, and Population Issues Research Center, The Pennsylvania State University, University Park, Pennsylvania, 16802, USA

    Clifford C. Clogg

  2. Department of Sociology, University of Arizona, Tucson, Arizona, 85721, USA

    James W. Shockey

Authors
  1. Clifford C. Clogg
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  2. James W. Shockey
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Editor information

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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© 1988 Plenum Press, New York

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Clogg, C.C., Shockey, J.W. (1988). Multivariate Analysis of Discrete Data. 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_10

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  • DOI: https://doi.org/10.1007/978-1-4613-0893-5_10

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8232-7

  • Online ISBN: 978-1-4613-0893-5

  • eBook Packages: Springer Book Archive

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