頁籤選單縮合
題 名 | Hierarchical Bayesian Analysis of Binary Matched Pairs Data |
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作 者 | Ghosh,Malay; Chen,Ming-hui; Ghosh,Atalanta; Agresti,Alan; | 書刊名 | Statistica Sinica |
卷 期 | 10:2 2000.04[民89.04] |
頁 次 | 頁647-657 |
分類號 | 319.5 |
關鍵詞 | Conditional maximum likelihood estimator; Gibbs sampling; Improper prior distribution; Logit model; Log-log model; Markov chain monte carlo; McNemar test; Probit model; |
語 文 | 英文(English) |
英文摘要 | The paper introduces a hierarchical Bayesian analysis of binary matched pairs data with noninformative prior distributions. Certain properties of the posterior distributions, including their propriety, are established. The Bayesian methods are implemented via Markov chain Monte Carlo integration techniques, and numerical illustrations are provided. For the logit link, the conditional and marginal maximum likelihood estimators of a treatment effect depend only on the off-main-diagonal elements of a 2×2 contingency table, and the same is true of McNemar’s test. By contrast, the hierarchical Bayes estimators and subsequent analyses depend also on the main-diagonal elements in a natural way. |
本系統中英文摘要資訊取自各篇刊載內容。