Recent Advances in Theory and Methods for the Analysis of Categorical Data: Making the Link to Statistical Practice.

Abstract

This paper reviews some of the general results on maximum likelihood estimation for loglinear models. These results have special relevance for the analysis of multidimensional contingency tables, and for the reporting of data from large-scale sample surveys. In addition, the results are applicable to other categorical data problems that are often representable in contingency table form.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA111016

Entities

People

  • Stephen E. Fienberg

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Cells
  • Computational Science
  • Data Analysis
  • Ethnic Groups
  • Maximum Likelihood Estimation
  • New York
  • Numerical Analysis
  • Probability
  • Random Variables
  • Sampling
  • Social Networks
  • Social Sciences
  • Statistics
  • Surveys
  • Three Dimensional
  • United States

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Systems Analysis and Design