A product-multinomial framework for categorical data analysis with missing responses
From MaRDI portal
Publication:2448571
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
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
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Missing data mechanisms and their implications on the analysis of categorical data
- Likelihood based frequentist inference when data are missing at random
- On the maximum-likelihood analysis of the general linear model in categorical data.
- Every Missingness not at Random Model Has a Missingness at Random Counterpart with Equal Fit
- Analysis of Categorical Data by Linear Models
- Categorical Data Analysis: Some Reflections on the Log Linear Model and Logistic Regression. Part I: Historical and Methodological Overview
- Two-Dimensional Contingency Tables with Both Completely and Partially Cross-Classified Data
- Inference and missing data
- Logistic regression for autocorrelated data with application to repeated measures
- The Score Test for Independence in R x C Contingency Tables with Missing Data
- 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
This page was built for publication: A product-multinomial framework for categorical data analysis with missing responses