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 2 x 2 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.
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机译:当个别信息不可用时,考虑相关二进制数据的贝叶斯分析。特别是,在两个不同的场合(通常是时间点),对两个独立组的相同受试者测量了二元结果。这些组是通过二元暴露或预后因素制定的。兴趣在于估计随时间变化的暴露和结果之间的关联。用于此目的的标准方法适用于单个项目响应,如果缺少这些方法,则是不够的。此外,假设唯一可用的信息是每种情况下分组变量和响应之间的边际2 x 2交叉表。假设两组的独立二项式分布,则基于相应的优势比,估计每种情况下的成功概率以及暴露与结果之间的关联。为了处理每个项目响应的缺失信息并估计相应的转移概率,采用了贝叶斯方法。
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