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Cited by 706Statistical Methods in EpidemiologyGlobal Cancer Incidence and ScreeningAdvanced Causal Inference Techniques

Case–Control Studies

Rothman, Kenneth J., Greenland, Sander, Lash, Timothy L.·2008·Encyclopedia of Quantitative Risk Analysis and Assessment
DOI 10.1002/9780470061596.risk0599
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Abstract

In a cohort study, the numerator and denominator of each disease frequency (incidence proportion, incidence rate, or incidence odds) are measured, which requires enumerating the entire population and keeping it under surveillance. A case‐control study observes the population more efficiently by using a sample of the population, which becomes the control series, in place of complete assessment of the denominators of the disease frequencies. This extra sampling step can make a case‐control study much more efficient than a cohort study of the same population, but it introduces a number of subtleties and avenues for bias that are absent in typical cohort studies. For diseases that are sufficiently rare, cohort studies become impractical, and case‐control studies become the only useful alternative. The cases in a case‐control study should be the same people who would be considered cases in a cohort study of the same population. The definition of the source population for these cases determines the population from which controls should be sampled. Ideally, control selection would involve direct sampling from the source population, with equal probability of selection, although in many circumstances, variations in and substitutes for this ideal sampling design may be considered.

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  • Causal information can sometimes be recovered despite direct selection on the outcome when certain constraints are imposed on the data.

    “We note that the recovery of causal information despite direct selection on the outcome is sometimes possible if certain constraints can be imposed on the data.”

    From Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable (2014) · cites this paper as Rothman et al. 2008

  • In case-control studies, observations should not be sampled as a function of both the treatment and the outcome.

    “A key rule in case-control studies, however, is that observations should not be sampled (ascertained) as a function of both the treatment and the outcome.”

    From Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable (2014) · cites this paper as Rothman et al. 2008

  • Violating the rule against sampling on both treatment and outcome produces ascertainment bias.

    “The consequence of violating this rule is known as ascertainment bias (Rothman et al. 2008).”

    From Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable (2014) · cites this paper as Rothman et al. 2008

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Authors
Rothman, K. J., Greenland, S., & Lash, T. L.
Affiliations
  • Boston University (US)
  • University of California, Los Angeles (US)
ORCID
Venue
Encyclopedia of Quantitative Risk Analysis and Assessment
Publisher
Wiley
Published
2008-07-15
DOI
10.1002/9780470061596.risk0599
OpenAlex
W1608258930
Cited by
706
References
2
Citations by year
2026: 2 · 2025: 4 · 2024: 10 · 2023: 11 · 2022: 9 · 2021: 19 · 2020: 19 · 2019: 16 · 2018: 24 · 2017: 19 · 2016: 26 · 2015: 37 · 2014: 60 · 2013: 62 · 2012: 42
Type
reference entry
Language
en
Open access
closed
Licence
doi.wiley.com/10.1002/tdm_license_1.1 (tdm)
Locations
Encyclopedia of Quantitative Risk Analysis and Assessment (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords
case-control study, cohort studies, research design, sampling bias, control selection, incidence estimation, rare diseases, learning efficiency

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