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Cited by 293Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyStatistical Methods in Clinical Trials

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

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Rose, Sherri, van der Laan, Mark J.·2009·The International Journal of Biostatistics
DOI 10.2202/1557-4679.1127PMC PMC2827892
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Abstract

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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Research works printed but not linked: 5

  1. The International Journal of Biostatistics, Vol. 5 [2009], Iss. 1, Art. 1 DOI: 10.2202/1557-4679.1127
  2. K. Rothman and S. Greenland. Modern Epidemiology. Lippincott, Williams and Wilkins, Philadelphia, PA, 2nd edition, 1998.
  3. D.B. Rubin. Matched Sampling for Causal Effects. Cambridge University Press, Cambridge, MA, 2006.
  4. M.J. van der Laan and J.M. Robins. Unified methods for censored longitudinal data and causailty. Springer, New York, 2002.
  5. The International Journal of Biostatistics, Vol. 5 [2009], Iss. 1, Art. 1 DOI: 10.2202/1557-4679.1127

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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)
DOI
10.2202/1557-4679.1127
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
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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