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Prescriptions for Working Statisticians pp 252–287Cite as

Analysis of Cross-Classified Data

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Abstract

Suppose we have a population wherein associated with each member of the population is characteristic from the set of r 1 characteristics \(c_{11},\ldots,c_{1r_{1}}\) and a characteristic from the set of r 2 characteristics \(c_{21},\ldots,c_{2r_{2}}\). For example, if the population is that of all adults (age 18 or over) in the United States, then characteristic 1 might be sex, so that r 1 = 2, c 11 = male, and c 12 = female, and characteristic 2 might be age, so that r 2 = 100, and c 21 = 18, c 22 = 19, …, C 2,100 = 117. We can associate with each member of the population the pair (i i , i 2), where i 1, denotes the index of characteristic 1 and i 2 denotes the index of characteristic 2 of that member.

“Old statisticians never die ... they just get broken down by age and sex.”

S. Smith

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Authors and Affiliations

  1. Graduate School of Business, University of Chicago, Chicago, IL, 60637, USA

    Albert Madansky

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  1. Albert Madansky
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© 1988 Springer-Verlag New York Inc.

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Madansky, A. (1988). Analysis of Cross-Classified Data. In: Prescriptions for Working Statisticians. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3794-5_9

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  • DOI: https://doi.org/10.1007/978-1-4612-3794-5_9

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-8354-6

  • Online ISBN: 978-1-4612-3794-5

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