Case-control matching: effects, misconceptions, and recommendations
Open accessAbstract
Misconceptions about the impact of case-control matching remain common. We discuss several subtle problems associated with matched case-control studies that do not arise or are minor in matched cohort studies: (1) matching, even for non-confounders, can create selection bias; (2) matching distorts dose-response relations between matching variables and the outcome; (3) unbiased estimation requires accounting for the actual matching protocol as well as for any residual confounding effects; (4) for efficiency, identically matched groups should be collapsed; (5) matching may harm precision and power; (6) matched analyses may suffer from sparse-data bias, even when using basic sparse-data methods. These problems support advice to limit case-control matching to a few strong well-measured confounders, which would devolve to no matching if no such confounders are measured. On the positive side, odds ratio modification by matched variables can be assessed in matched case-control studies without further data, and when one knows either the distribution of the matching factors or their relation to the outcome in the source population, one can estimate and study patterns in absolute rates. Throughout, we emphasize distinctions from the more intuitive impacts of cohort matching.
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Matching is particularly relevant when the distribution of important confounders differs substantially between cases and unmatched controls.
“Matching is particularly relevant in situations in which the distribution of important confounders differs substantially between cases and unmatched controls [48].”
From COSMOS-E: Guidance on conducting systematic reviews and meta-analyses of observational studies of etiology (2019) · cites this paper as [48]
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- Authors
- Mansournia, M. A., Jewell, N. P., & Greenland, S.
- Affiliations
- University of California, Berkeley (US)
- University of California, Los Angeles (US)
- Venue
- European Journal of Epidemiology
- Published
- 2017-11-03
- Volume
- 33
- Issue
- 1
- Pages
- 5-14
- ISSN
- 0393-2990 (ISSN-L)
- 1573-7284
- PMC
- PMC9188848
- OpenAlex
- W2765263492
- Cited by
- 175
- References
- 53
- Citations by year
- 2026: 16 · 2025: 23 · 2024: 21 · 2023: 24 · 2022: 26 · 2021: 25 · 2020: 18 · 2019: 11 · 2018: 10 · 2017: 1
- FWCI
- 7.61
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- European Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of Allergy and Infectious Diseases (R56AI134724)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- case-control matching, selection bias, residual confounding, statistical power, odds ratio estimation, matched cohort, confounder selection
- MeSH terms
- Humans, Research Design, Cohort Studies, Bias, Confounding Factors, Epidemiologic, Odds Ratio, Case-Control Studies, Matched-Pair Analysis
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