Whitehead A, Omar R Z, Higgins J P, Savaluny E, Turner R M, Thompson S G
Medical and Pharmaceutical Statistics Research Unit, The University of Reading, P.O. Box 240, Earley Gate, Reading RG6 6FN, U.K.
Stat Med. 2001 Aug 15;20(15):2243-60. doi: 10.1002/sim.919.
Meta-analyses are being undertaken in an increasing diversity of diseases and conditions, some of which involve outcomes measured on an ordered categorical scale. We consider methodology for undertaking a meta-analysis on individual patient data for an ordinal response. The approach is based on the proportional odds model, in which the treatment effect is represented by the log-odds ratio. A general framework is proposed for fixed and random effect models. Tests of the validity of the various assumptions made in the meta-analysis models, such as a global test of the assumption of proportional odds between treatments, are presented. The combination of studies with different definitions or numbers of response categories is discussed. The methods are illustrated on two data sets, in a classical framework using SAS and MLn and in a Bayesian framework using BUGS. The relative merits of the three software packages for such meta-analyses are discussed.
荟萃分析正应用于越来越多不同的疾病和病症，其中一些涉及按有序分类尺度测量的结果。我们考虑对个体患者数据进行有序反应的荟萃分析方法。该方法基于比例优势模型，其中治疗效果由对数优势比表示。提出了固定效应模型和随机效应模型的一般框架。给出了对荟萃分析模型中各种假设有效性的检验，例如治疗之间比例优势假设的全局检验。讨论了具有不同反应类别定义或数量的研究的合并。在两个数据集上说明了这些方法，一个是在使用SAS和MLn的经典框架中，另一个是在使用BUGS的贝叶斯框架中。讨论了这三个软件包用于此类荟萃分析的相对优点。
