文章基本信息

标题：Reusable, set-based selection algorithm for matched control groups
本地全文：下载
作者：Daniel Thayer ; John W Gregory ; Liv Kosnes 等
期刊名称：International Journal of Population Data Science
电子版ISSN：2399-4908
出版年度：2017
卷号：1
期号：1
页码：1-1
DOI：10.23889/ijpds.v1i1.395
出版社：Swansea University
摘要：99.99% of the matched controls had a week of birth that was identical to the subject. The second example was a matched cohort study looking at hospital admissions and type 1 diabetes, using the Brecon register of childhood diabetes in Wales, with matching based on week of birth within two weeks, gender, county of residence, deprivation quintile, and residence in Wales at time of diagnosis. This study had a matching rate of 98.9%; 97.5% of subjects matched to five controls, and 69.8% of matches had the same week of birth. ConclusionsThis algorithm provides good matching performance while executing efficiently and scalably on large datasets. Its implementation as reusable code will facilitate more efficient, high-quality research in SAIL. Instead of spending many hours developing a custom solution, analysts can execute parameterized code in a few minutes. We hope it to be useful more widely beyond SAIL as well.