Automated Name Selection for the Network Scale-up Method

Adrià Fenoy, Michał Bojanowski, Miranda J. Lubbers
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Abstract

To estimate the distribution of the number of acquaintances of the members of a society, the network scale-up method asks survey respondents about the number of people they know with features for which national statistics are available. While many features have been used for this purpose, first names have been suggested to produce particularly low levels of transmission error and recall bias. For this method to be precise, a set of names needs to be selected for the survey that jointly represents the population in relevant variables such as gender or age. This article provides a solution approach to finding the optimal set of names. This can be applied to any population for which a joint distribution of first names and relevant variables is available. We show that our approach successfully provides sets of names closely mirroring the population distributions for six countries with different name statistics.
为网络扩展法自动选择名称
为了估算社会成员熟人数量的分布情况,网络扩展法向调查对象询问他们所认识的人的数量,这些人的特征有国家统计数据可查。虽然有许多特征被用于此目的,但有人认为名字产生的传播误差和回忆偏差特别小。为使这一方法精确,需要为调查选择一组姓名,以共同代表性别或年龄等相关变量的人口。本文提供了一种寻找最佳名称集的解决方法。该方法适用于任何可以获得姓名和相关变量联合分布的人群。我们的研究表明,我们的方法成功地为六个具有不同姓名统计数据的国家提供了与人口分布密切相关的姓名集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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