A product-multinomial framework for categorical data analysis with missing responses

DOI10.1214/12-BJPS198zbMath1426.62012OpenAlexW2003217358WikidataQ57588050 ScholiaQ57588050MaRDI QIDQ2448571

Frederico Z. Poleto, Julio da Motta Singer, Carlos Daniel M. Paulino

Publication date: 2 May 2014

Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.bjps/1391611341

zbMATH Keywords

EM algorithmincomplete datamissing dataselection modelsmissingness mechanism

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Parametric inference under constraints (62F30)

Related Items (4)

On log-linear modeling for an incomplete two-way contingency table with one variable subject to nonresponse ⋮ Bayesian comparison of diagnostic tests with largely non-informative missing data ⋮ Comparing diagnostic tests with missing data ⋮ A general GEE framework for the analysis of longitudinal ordinal missing data and related issues

Uses Software

• R

Cites Work

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• Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part II: Data Analysis
• Weighted Least Squares Analysis of Repeated Categorical Measurements with Outcomes Subject to Nonresponse
• Models for Three-Dimensional Contingency Tables with Completely and Partially Cross-Classified Data
• Multinomial Sampling with Partially Categorized Data
• Maximum Likelihood Estimation with Incomplete Multinomial Data

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