Fosgate G T
Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843-4458, USA.
J Clin Epidemiol. 2007 Mar;60(3):250-5. doi: 10.1016/j.jclinepi.2006.06.010. Epub 2006 Sep 28.
The objective of the paper was to design a computer algorithm to calculate sample sizes for estimating proportions incorporating clustered sampling units using a beta-binomial model when information concerning the intraclass correlation is not available.
A computer algorithm was written in FORTRAN and evaluated for a hypothetical sample size situation.
The developed algorithm was able to incorporate clustering in estimated sample sizes through the specification of a beta distribution to account for within-cluster correlation. In a hypothetical example, the usual normal approximation method for estimation of a proportion ignoring the clustered sampling design resulted in a calculated sample size of 107, whereas the developed algorithm suggested that 208 sampling units would be necessary.
It is important to incorporate cluster adjustment in sample size calculations when designing epidemiologic studies for estimation of disease burden and other population proportions in the situation of correlated data even when information concerning the intraclass correlation is not available. Beta-binomial models can be used to account for clustering, and design effects can be estimated by generating beta distributions that encompass within-cluster correlation.
本文的目的是设计一种计算机算法，用于在无法获得关于组内相关信息的情况下，使用β-二项式模型计算包含整群抽样单元的估计比例的样本量。
用FORTRAN编写了一种计算机算法，并针对假设的样本量情况进行了评估。
所开发的算法能够通过指定β分布来考虑群内相关性，从而将整群效应纳入估计的样本量中。在一个假设示例中，忽略整群抽样设计的用于估计比例的常用正态近似方法得出的计算样本量为107，而所开发的算法表明需要208个抽样单元。
在设计用于估计疾病负担和其他人群比例的流行病学研究时，即使无法获得关于组内相关的信息，在相关数据情况下进行样本量计算时纳入整群调整也很重要。β-二项式模型可用于考虑整群效应，并且可以通过生成包含群内相关性的β分布来估计设计效应。
