The DOI matches its Crossref record; 39 of the 40 references it cites were found in a registry or an index.
Why Match? Investigating Matched Case-Control Study Designs with Causal Effect Estimation
Open accessAbstract
Matched case-control study designs are commonly implemented in the field of public health. While matching is intended to eliminate confounding, the main potential benefit of matching in case-control studies is a gain in efficiency. Methods for analyzing matched case-control studies have focused on utilizing conditional logistic regression models that provide conditional and not causal estimates of the odds ratio. This article investigates the use of case-control weighted targeted maximum likelihood estimation to obtain marginal causal effects in matched case-control study designs. We compare the use of case-control weighted targeted maximum likelihood estimation in matched and unmatched designs in an effort to explore which design yields the most information about the marginal causal effect. The procedures require knowledge of certain prevalence probabilities and were previously described by van der Laan (2008). In many practical situations where a causal effect is the parameter of interest, researchers may be better served using an unmatched design.
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“To ensure that the effects observed were not confounded by other factors, we matched the services that implemented the AI-enabled self-referral tool to other similar services as commonly done in similar clinical and public health research studies [Rose and Van der Laan, 2009].”
From Closing the accessibility gap to mental health treatment with a personalized self-referral chatbot (2024) · cites this paper as Rose and Van der Laan, 2009
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Targeted Maximum Likelihood Learning
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Research works printed but not linked: 5
- The International Journal of Biostatistics, Vol. 5 [2009], Iss. 1, Art. 1 DOI: 10.2202/1557-4679.1127
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- The International Journal of Biostatistics, Vol. 5 [2009], Iss. 1, Art. 1 DOI: 10.2202/1557-4679.1127
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Lonsdorf, T. B., Menz, M. M., Andreatta, M., Fullana, M. A., Golkar, A., Haaker, J., Heitland, I., Hermann, A., Kuhn, M., Kruse, O., et al. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.02.026 · Cited by 837
Dominant modifiable risk factors for stroke in Ghana and Nigeria (SIREN): a case-control study
Owolabi, M. O., Sarfo, F. S., Akinyemi, R., Gebregziabher, M., Akpa, O. M., Akpalu, A. K., Wahab, K., Obiako, R., Owolabi, L. F., Ovbiagele, B. I., et al. (2018) · The Lancet Global Health · doi:10.1016/s2214-109x(18)30002-0 · Cited by 313
Targeted Maximum Likelihood Based Causal Inference: Part II
van der Laan, M. J. (2010) · The International Journal of Biostatistics · doi:10.2202/1557-4679.1241 · Cited by 239
Tougui, I., Jilbab, A., & Mhamdi, J. E. (2021) · Healthcare Informatics Research · doi:10.4258/hir.2021.27.3.189 · Cited by 199
Reisner, S. L., Hughto, J. M. W., Bradford, J., & Mimiaga, M. J. (2014) · LGBT Health · doi:10.1089/lgbt.2014.0009 · Cited by 224
Metadata
- Authors
- Rose, S., & van der Laan, M. J.
- Affiliations
- University of California, Berkeley (US)
- University of California, Berkeley
- ORCID
- Rose, Sherri
- Venue
- The International Journal of Biostatistics
- Publisher
- Walter de Gruyter GmbH
- Published
- 2009-01-06
- Volume
- 5
- Issue
- 1
- Pages
- Article 1-Article 1
- ISSN
- 1557-4679 (ISSN-L)
- PMC
- PMC2827892
- OpenAlex
- W2059121696
- Cited by
- 293
- References
- 40
- Citations by year
- 2026: 3 · 2025: 16 · 2024: 27 · 2023: 20 · 2022: 24 · 2021: 27 · 2020: 26 · 2019: 25 · 2018: 25 · 2017: 24 · 2016: 16 · 2015: 15 · 2014: 14 · 2013: 8 · 2012: 9
- FWCI
- 4.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The International Journal of Biostatistics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Collection of Biostatistics Research Archive (COBRA) (submittedVersion)
- Funders
- National Institutes of Health (R01 A1074345-01)
- U.S. Public Health Service (R01 A1074345-01)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- matched case-control studies, causal effect estimation, targeted maximum likelihood estimation, conditional logistic regression, confounding
- MeSH terms
- Humans, Research Design, Models, Statistical, Causality, Likelihood Functions, Case-Control Studies
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