Contingency Tables

  • J. D. Jobson
Part of the Springer Texts in Statistics book series (STS)


This chapter begins with an introduction for Volume II and then presents a survey of the techniques available for analyzing contingency tables. The introduction consists of a discussion of data matrices measurement scales and an outline of techniques presented in Volume II. The discussion of contingency tables begins in the second section with a review of bivariate analysis for two categorical random variables and includes a discussion of inference techniques for two-dimensional tables. The discussion of two-dimensional tables also includes an introduction to the use of loglinear models. The third section presents a discussion of the application of loglinear models to multidimensional tables based on the maximum likelihood approach to estimation. The logit model is also introduced as a special case of the loglinear model. The last section of the chapter outlines the weighted least squares approach to modeling categorical data. The weighted least squares approach affords a greater variety of models than the maximum likelihood method.


Contingency Table Driver Condition Loglinear Model Marginal Density Injury Category 
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 Science+Business Media New York 1992

Authors and Affiliations

  • J. D. Jobson
    • 1
  1. 1.Faculty of BusinessUniversity of AlbertaEdmontonCanada

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