Bayesian analysis of two dependent 2×2 contingency tables

Bayesian analysis of correlated binary data when individual information is not available is considered. In particular, a binary outcome is measured on the same subjects of two independent groups at two separate occasions (usually time points). The groups are formulated through a binary exposure or a prognostic factor. Interest lies in estimating the association between exposure and outcome over time. Standard methods for this purpose apply on the individual item responses and are insufficient in case these are missing. Moreover it is assumed that the only available information is the marginal 2x2 cross-tabulations between the grouping variable and the response for each occasion. Assuming independent binomial distributions for the two groups, the success probabilities for each occasion as well as the associations between exposure and outcome, based on the corresponding odds ratios, are estimated. In order to deal with the missing information of each item's response and to estimate the corresponding transition probabilities, a Bayesian procedure is adopted.

[1]  María José García-Zattera,et al.  A Dirichlet process mixture model for the analysis of correlated binary responses , 2007, Comput. Stat. Data Anal..

[2]  Jun S. Liu,et al.  Monte Carlo strategies in scientific computing , 2001 .

[3]  J. Geweke,et al.  Bayesian Inference in Econometric Models Using Monte Carlo Integration , 1989 .

[4]  D. Dockery,et al.  Passive smoking, gas cooking, and respiratory health of children living in six cities. , 2015, The American review of respiratory disease.

[5]  Xiao-Li Meng,et al.  Posterior Predictive $p$-Values , 1994 .

[6]  N. Laird,et al.  A likelihood-based method for analysing longitudinal binary responses , 1993 .

[7]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[8]  J G Liao,et al.  A Hierarchical Bayesian Model for Combining Multiple 2 × 2 Tables Using Conditional Likelihoods , 1999, Biometrics.

[9]  Nian-Sheng Tang,et al.  Testing the equality of proportions for correlated otolaryngologic data , 2008, Comput. Stat. Data Anal..

[10]  W. Wong,et al.  The calculation of posterior distributions by data augmentation , 1987 .

[11]  John M. Olin On MCMC sampling in hierarchical longitudinal models , 1999 .

[12]  Stephen E. Fienberg,et al.  Making the Release of Confidential Data from Multi-Way Tables Count , 2004 .

[13]  Ming Tan,et al.  Hierarchical models for repeated binary data using the IBF sampler , 2006, Comput. Stat. Data Anal..

[14]  Alan Agresti,et al.  Multivariate tests comparing binomial probabilities, with application to safety studies for drugs , 2005 .

[15]  M D Begg,et al.  Analyzing k (2 × 2) Tables Under Cluster Sampling , 1999, Biometrics.