ArticleAnnals of epidemiology2023
A flexible matching strategy for matched nested case-control studies.
Article in Annals of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- Exploring the Time to Onset and Early Predictors of Poststroke Spasticity Combined With Surface Electromyography: Protocol for a Nested Case-Control Study.JMIR research protocols · 2025Article
- Cross-Cultural Validation of the Thai Oral Health Impact Profile for Temporomandibular Disorders.International dental journal · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
purposeIndividual matching in case-control studies improves statistical efficiency over random selection of controls but can lead to selection bias if cases are excluded due to the lack of appropriate controls or residual confounding with less strict matching criteria. We introduce flex matching, an algorithm using multiple rounds of control selection with successively relaxed matching criteria to select controls for cases.
methodsWe simulated exposure-disease relationships in multiple cohort data sets with a range of confounding scenarios and conducted 16,800,000 nested case-control studies, comparing random selection of controls, strict matching, and flex matching. We computed average bias and statistical efficiency in estimates of exposure-disease relationships under each matching strategy.
resultsOn average, flex matching produced the least biased estimates of exposure-disease associations with the smallest standard errors. Strict matching algorithms that excluded cases for whom matched controls could not be identified produced biased estimates with larger standard errors. Estimates from studies with random assignment of controls were relatively unbiased, but the standard errors were larger than from studies using flex matching.
conclusionsFlex matching should be considered for case-control designs, especially for biomarker studies where matching on technical artifacts is necessary and maximizing efficiency is a priority.
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