Gray R J
Department of Biostatistics, Dana-Farber Cancer Institute, Boston, Massachusetts.
Biometrics. 1994 Mar;50(1):244-53.
This paper examines a Bayesian method for investigating the amount of institutional variation in a multicenter clinical trial with a censored failure time endpoint. A hierarchical structure is used to model the institutional effects in a proportional hazards model, with the posterior distributions calculated using Gibbs sampling. The methods are applied to data from a lung cancer trial conducted by the Eastern Cooperative Oncology Group. In this trial there appears to be substantial variation in the treatment effect across institutions. Although the reasons for this have been identified, it would be possible to investigate this further through a detailed examination of the data from institutions with extreme effects.
本文研究了一种贝叶斯方法，用于在具有删失失效时间终点的多中心临床试验中调查机构间的差异量。使用分层结构在比例风险模型中对机构效应进行建模，并使用吉布斯抽样计算后验分布。这些方法应用于东部肿瘤协作组开展的一项肺癌试验的数据。在该试验中，各机构间的治疗效果似乎存在很大差异。尽管已找出造成这种情况的原因，但仍有可能通过详细检查具有极端效应的机构的数据来进一步调查这一情况。
