Bilder Christopher R, Zhang Boan, Schaarschmidt Frank, Tebbs Joshua M
Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE.
R J. 2010 Dec 1;2(2):56-60.
When the prevalence of a disease or of some other binary characteristic is small, group testing (also known as pooled testing) is frequently used to estimate the prevalence and/or to identify individuals as positive or negative. We have developed the binGroup package as the first package designed to address the estimation problem in group testing. We present functions to estimate an overall prevalence for a homogeneous population. Also, for this setting, we have functions to aid in the very important choice of the group size. When individuals come from a heterogeneous population, our group testing regression functions can be used to estimate an individual probability of disease positivity by using the group observations only. We illustrate our functions with data from a multiple vector transfer design experiment and a human infectious disease prevalence study.
当某种疾病或其他二元特征的患病率较低时，分组检测（也称为混合检测）经常被用于估计患病率和/或识别个体的阳性或阴性状态。我们开发了binGroup软件包，这是第一个旨在解决分组检测中估计问题的软件包。我们提供了用于估计同质人群总体患病率的函数。此外，对于这种情况，我们还有一些函数来辅助进行非常重要的组大小选择。当个体来自异质人群时，我们的分组检测回归函数可用于仅通过组观察来估计个体疾病阳性的概率。我们用来自多载体转移设计实验和人类传染病患病率研究的数据来说明我们的函数。
