Using imputation to provide location information for nongeocoded addresses.
Using imputation to provide location information for nongeocoded addresses.
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DOI：
10.1371/journal.pone.0008998
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发表时间：
2010-02-10
期刊：
影响因子：
3.7
通讯作者：
Klassen AC
中科院分区：
文献类型：
--
作者：
Curriero FC;Kulldorff M;Boscoe FP;Klassen AC
地理作为健康研究变异来源的重要性在文献中继续受到持续的关注。在这类研究中包含地理信息通常是从向地图中添加数据开始的，而地图是由一些位置知识预测的。精确的空间信息通常是通过地理编码实现的，地理编码是地理信息系统（GIS）将邮寄地址信息转换为地图上的坐标的过程。然而，地理编码过程并非没有其局限性，因为总有一定比例的地址无法成功转换（不可地理编码）。这引起了对偏见的担忧，因为传统的做法是将非地理编码的数据记录排除在分析之外。在本文中，我们开发和评估了一套用于处理来自非地理编码地址的缺失空间信息的imputation策略。这些策略的制定是假设一个已知的邮政编码，并越来越多地使用附带信息，即处于危险中的人口的空间分布。使用从马里兰州癌症登记处获得的前列腺癌数据来评估策略。在应用和评估这些方法时，我们考虑了人口普查县、地区和街区组水平的总病例计数作为感兴趣的结果。多重输入用于提供基于完整数据（地理编码加上输入的非地理编码）的估计总病例数，并具有一定的不确定性。结果表明，基于可用人口的年龄、性别和种族信息的归责策略在县、区和街区组水平上的总体效果最好。该程序允许仅基于地理编码记录的病例枚举以统计调整计数（估算计数）和基于所有病例数据、地理编码和估算的非地理编码的不确定性度量来呈现可能存在偏差和可能未报告的结果。类似的策略可以应用于其他分析设置。
The importance of geography as a source of variation in health research continues to receive sustained attention in the literature. The inclusion of geographic information in such research often begins by adding data to a map which is predicated by some knowledge of location. A precise level of spatial information is conventionally achieved through geocoding, the geographic information system (GIS) process of translating mailing address information to coordinates on a map. The geocoding process is not without its limitations, though, since there is always a percentage of addresses which cannot be converted successfully (nongeocodable). This raises concerns regarding bias since traditionally the practice has been to exclude nongeocoded data records from analysis. In this manuscript we develop and evaluate a set of imputation strategies for dealing with missing spatial information from nongeocoded addresses. The strategies are developed assuming a known zip code with increasing use of collateral information, namely the spatial distribution of the population at risk. Strategies are evaluated using prostate cancer data obtained from the Maryland Cancer Registry. We consider total case enumerations at the Census county, tract, and block group level as the outcome of interest when applying and evaluating the methods. Multiple imputation is used to provide estimated total case counts based on complete data (geocodes plus imputed nongeocodes) with a measure of uncertainty. Results indicate that the imputation strategy based on using available population-based age, gender, and race information performed the best overall at the county, tract, and block group levels. The procedure allows for the potentially biased and likely under reported outcome, case enumerations based on only the geocoded records, to be presented with a statistically adjusted count (imputed count) with a measure of uncertainty that are based on all the case data, the geocodes and imputed nongeocodes. Similar strategies can be applied in other analysis settings.
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