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2002•Wiley series in probability and statisticsRequires access

Analyzing Repeated Categorical Response Data

Alan Agresti

Open publisher page 13 citations

Abstract

Chapter 11 focuses on methods of analyzing repeated categorical response data, with emphasis on marginal models. It presents both the maximum likelihood approach and the generalized estimating equations (GEE) approach to marginal modeling. It also discusses quasi likelihood in greater detail and shows how GEE is a multivariate version of it. The chapter ends with discussion of Markov Chain models for transitional modeling.

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What this paper is about

Chapter 11 focuses on methods of analyzing repeated categorical response data, with emphasis on marginal models. It presents both the maximum likelihood approach and the generalized estimating equations (GEE) approach to marginal modeling. It also discusses quasi likelihood in greater detail and shows how GEE is a multivariate version of it. The chapter ends with discussion of Markov Chain models for transitional modeling.

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OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Chapter 11 focuses on methods of analyzing repeated categorical response data, with emphasis on marginal models. It presents both the maximum likelihood approach and the generalized estimating equations (GEE) approach to marginal modeling. It also discusses quasi likelihood in greater detail and shows how GEE is a multivariate version of it. The chapter ends with discussion of Markov Chain models for transitional modeling.

Key concepts: Categorical variable, Gee, Generalized estimating equation, Marginal model, Multivariate statistics, Markov chain, Mathematics, Statistics

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