Dynamic association modeling in \(2\times 2\) contingency tables

DOI10.1016/j.stamet.2010.10.002zbMath1213.62103OpenAlexW1975564639MaRDI QIDQ537481

M. Alijani, Seyed Kamran Ghoreishi

Publication date: 20 May 2011

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2010.10.002

zbMATH Keywords

Markov processesgenetic algorithmMCMC method

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Bayesian inference (62F15) Approximation methods and heuristics in mathematical programming (90C59) Contingency tables (62H17)

Related Items (2)

Dynamic Bayesian analysis of generalized odds ratios assuming multivariate skew-normal distribution for the error terms in the system equation ⋮ Phase-II monitoring and diagnosing of multivariate categorical processes using generalized linear test-based control charts

Cites Work

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• Bayesian inference for categorical data analysis
• Bayesian estimation of unrestricted and order-restricted association models for a two-way contingency table
• Prediction and classification of non-stationary categorical time series
• Regression theory for categorical time series
• Regression models for nonstationary categorical time series: Asymptotic estimation theory
• Pseudotable methods for the analysis of \(2\times 2\) tables
• A Median-Unbiased Estimator of the AR(1) Coefficient
• A bayesian test for a two-way contingency table using independence priors
• Empirical bayes estimation of the log odds ratio in 2×2 contingency tables
• Optimal allocation for Bayesian inference about an odds ratio
• Bayesian estimation of odds ratios under prior hypotheses of independence and exchangeability
• Bayesian Testing and Estimation of Association in a Two-Way Contingency Table
• Bayesian Measures of Model Complexity and Fit
• REGRESSION MODELS FOR NON‐STATIONARY CATEGORICAL TIME SERIES
• Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
• Bayesian selection of log‐linear models
• Bayesian Estimation Methods for 2 × 2 Contingency Tables Using Mixtures of Dirichlet Distributions

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