连接美国历史普查的新策略:IPUMS 多代纵向面板案例研究》。

IF 1.6 2区 历史学 Q1 HISTORY
Historical Methods Pub Date : 2022-01-01 Epub Date: 2021-11-11 DOI:10.1080/01615440.2021.1985027
Jonas Helgertz, Joseph Price, Jacob Wellington, Kelly J Thompson, Steven Ruggles, Catherine A Fitch
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引用次数: 0

摘要

本文介绍了一种记录链接的概率方法,该方法是利用美国 1900 年和 1910 年的全面计数人口普查开发的,但适用于许多数字化历史记录来源。该方法采用两步法将记录联系起来,首先利用一整套个人和背景特征在男性中建立高置信度的匹配。然后,该方法利用在第一步中建立的家庭之间的联系,将男性和女性联系起来。虽然只有第一阶段的链接可以直接与美国研究中的其他流行方法进行比较,但我们的方法可以获得更高的链接率和更高的准确性,同时在与目标人群的相似性方面仅比其他算法差一点,可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A New Strategy for Linking U.S. Historical Censuses: A Case Study for the IPUMS Multigenerational Longitudinal Panel.

A New Strategy for Linking U.S. Historical Censuses: A Case Study for the IPUMS Multigenerational Longitudinal Panel.

A New Strategy for Linking U.S. Historical Censuses: A Case Study for the IPUMS Multigenerational Longitudinal Panel.

This paper presents a probabilistic method of record linkage, developed using the U.S. full count censuses of 1900 and 1910 but applicable to many sources of digitized historical records. The method links records using a two-step approach, first establishing high confidence matches among men by exploiting a comprehensive set of individual and contextual characteristics. The method then proceeds to link both men and women by leveraging links between households established in the first step. While only the first stage links can be directly comparable to other popular methods in research on the U.S., our method yields both considerably higher linkage rates and greater accuracy while only performing negligibly worse than other algorithms in resembling the target population.

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来源期刊
Historical Methods
Historical Methods Multiple-
CiteScore
3.20
自引率
7.10%
发文量
13
期刊介绍: Historical Methodsreaches an international audience of social scientists concerned with historical problems. It explores interdisciplinary approaches to new data sources, new approaches to older questions and material, and practical discussions of computer and statistical methodology, data collection, and sampling procedures. The journal includes the following features: “Evidence Matters” emphasizes how to find, decipher, and analyze evidence whether or not that evidence is meant to be quantified. “Database Developments” announces major new public databases or large alterations in older ones, discusses innovative ways to organize them, and explains new ways of categorizing information.
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