Chen Haiying, Stasny Elizabeth A, Wolfe Douglas A
Department of Public Health Sciences, Wake Forest University, Winston Salem, NC 27157, USA.
Stat Med. 2005 Nov 15;24(21):3319-29. doi: 10.1002/sim.2158.
Ranked set sampling (RSS) is a sampling procedure that can be considerably more efficient than simple random sampling (SRS). It involves preliminary ranking of the variable of interest to aid in sample selection. Although ranking processes for continuous variables that are implemented through either subjective judgement or via the use of a concomitant variable have been studied extensively in the literature, the use of RSS in the case of a binary variable has not been investigated thoroughly. In this paper we propose the use of logistic regression to aid in the ranking of a binary variable of interest. We illustrate the application of RSS to estimation of a population proportion with an example based on the National Health and Nutrition Examination Survey III data set. Our results indicate that this use of logistic regression improves the accuracy of the preliminary ranking in RSS and leads to substantial gains in precision for estimation of a population proportion.
秩集抽样（RSS）是一种抽样程序，它可比简单随机抽样（SRS）更高效。它涉及对感兴趣变量进行初步排序，以辅助样本选择。尽管通过主观判断或使用伴随变量对连续变量进行排序的过程在文献中已有广泛研究，但二元变量情况下的秩集抽样应用尚未得到充分研究。在本文中，我们提出使用逻辑回归来辅助对感兴趣的二元变量进行排序。我们基于第三次全国健康和营养检查调查数据集，通过一个例子说明了秩集抽样在总体比例估计中的应用。我们的结果表明，这种逻辑回归的应用提高了秩集抽样中初步排序的准确性，并在总体比例估计的精度上带来了显著提升。
