Ohlssen D I, Sharples L D, Spiegelhalter D J
MRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK.
Stat Med. 2007 Apr 30;26(9):2088-112. doi: 10.1002/sim.2666.
Random effects models are used in many applications in medical statistics, including meta-analysis, cluster randomized trials and comparisons of health care providers. This paper provides a tutorial on the practical implementation of a flexible random effects model based on methodology developed in Bayesian non-parametrics literature, and implemented in freely available software. The approach is applied to the problem of hospital comparisons using routine performance data, and among other benefits provides a diagnostic to detect clusters of providers with unusual results, thus avoiding problems caused by masking in traditional parametric approaches. By providing code for Winbugs we hope that the model can be used by applied statisticians working in a wide variety of applications.
随机效应模型在医学统计学的许多应用中都有使用，包括荟萃分析、整群随机试验以及医疗服务提供者的比较。本文基于贝叶斯非参数文献中所发展的方法，并在免费可用软件中实现，提供了一个关于灵活随机效应模型实际应用的教程。该方法应用于利用常规绩效数据进行医院比较的问题，除其他优点外，还提供了一种诊断方法来检测结果异常的医疗服务提供者集群，从而避免传统参数方法中因掩盖效应而导致的问题。通过提供Winbugs代码，我们希望该模型能被从事各种应用的应用统计学家所使用。
