An approximate maximum likelihood procedure for parameter estimation in multivariate discrete data regression models

DOI10.1080/02664760020016163zbMath0992.62049OpenAlexW2094254007MaRDI QIDQ4540853

Andrew Roddam

Publication date: 28 July 2002

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760020016163

Mathematics Subject Classification ID

Related Items (1)

Parameterizations and Fitting of Bi‐directed Graph Models to Categorical Data

Cites Work

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• Models for Longitudinal Data: A Generalized Estimating Equation Approach
• An approximation to maximum likelihood estimates in reduced models
• Analysis of Categorical Data by Linear Models
• A class of regression models for multivariate categorical responses
• On the Application of Conditional Independence to Ordinal Data
• A likelihood-based method for analysing longitudinal binary responses

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