The Network Scale-up Method (NSUM) uses social networks and answers to "How many X's do you know?" questions to estimate sizes of groups excluded by standard surveys. This paper addresses the bias caused by varying average social network sizes across populations, commonly referred to as the degree ratio bias. This bias is especially important for marginalized populations like sex workers and drug users, where members tend to have smaller social networks than the average person. We show how the degree ratio affects size estimates and provide a method to estimate degree ratios without collecting additional data. We demonstrate that our adjustment procedure improves the accuracy of NSUM size estimates using simulations and data from two data sources.

翻译：网络规模推算法（NSUM）利用社交网络和对“你认识多少位X类型的人？”问题的回答，来估计被标准调查排除在外的群体规模。本文研究因不同群体平均社交网络规模差异所引起的偏差，通常称为度数比例偏差。这种偏差对性工作者和吸毒者等边缘化群体尤为重要，因为这类群体的成员通常比普通人的社交网络更小。我们展示了度数比例如何影响规模估计，并提供了无需额外收集数据即可估计度数比例的方法。通过模拟实验和来自两个数据源的数据，我们证明了所提出的调整程序能够提高NSUM规模估计的准确性。