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Analysis of Cross-Classified Data

  • Albert Madansky
Part of the Springer Texts in Statistics book series (STS)

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.

Keywords

Contingency Table Latent Class Latent Class Analysis Royal Statistical Society Latent Class Model 
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. 1988

Authors and Affiliations

  • Albert Madansky
    • 1
  1. 1.Graduate School of BusinessUniversity of ChicagoChicagoUSA

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