Branscum Adam J, Johnson Wesley O, Gardner Ian A
Department of Biostatistics and Statistics, University of Kentucky, Lexington, 40506, USA.
Stat Med. 2006 Aug 15;25(15):2658-74. doi: 10.1002/sim.2449.
We developed a Bayesian approach to sample size calculations for studies designed to estimate disease prevalence that uses a hierarchical model for estimating the proportion of infected clusters (cluster-level prevalence) within a country or region. The clusters may, for instance, be villages within a region, cities within a state, or herds within a country. Our model allows for clusters with zero prevalence and for variability in prevalences among infected clusters. Moreover, uncertainty about diagnostic test accuracy and within-cluster prevalences is accounted for in the model. A predictive approach is used to address the issue of sample size selection in human and animal health surveys. We present sample size calculations for surveys designed to substantiate freedom of a region from an infectious agent (disease freedom surveys) and for surveys designed to estimate cluster-level prevalence of an endemic disease (prevalence estimation surveys). In disease freedom surveys, for instance, assuming the cluster-level prevalence for a particular infectious agent in the region is greater than a maximum acceptable threshold, a sample size combination consisting of the number of clusters sampled and number of subjects sampled per cluster can be determined for which authorities conducting the survey detect this excessive cluster-level prevalence with high predictive probability. The method is straightforward to implement using the Splus/R library emBedBUGS together with WinBUGS.
我们开发了一种贝叶斯方法，用于为旨在估计疾病患病率的研究计算样本量，该方法使用分层模型来估计一个国家或地区内受感染集群的比例（集群层面的患病率）。例如，集群可以是一个地区内的村庄、一个州内的城市或一个国家内的畜群。我们的模型允许存在患病率为零的集群，也允许受感染集群之间的患病率存在差异。此外，模型中考虑了诊断测试准确性和集群内患病率的不确定性。在人类和动物健康调查中，采用预测方法来解决样本量选择问题。我们给出了为证实一个地区不存在某种传染源而设计的调查（疾病无流行调查）以及为估计一种地方病的集群层面患病率而设计的调查（患病率估计调查）的样本量计算方法。例如，在疾病无流行调查中，假设该地区某种特定传染源的集群层面患病率高于最大可接受阈值，那么可以确定一个由抽样集群数量和每个集群抽样对象数量组成的样本量组合，通过该组合进行调查的当局能够以高预测概率检测到这种过高的集群层面患病率。使用Splus/R库emBedBUGS和WinBUGS一起，该方法很容易实现。
