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Updated: Jun 1, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Collapsibility in case-control studies.

Neil Pearce1

  • 1Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

International Journal of Epidemiology
|May 30, 2026
PubMed
Summary
This summary is machine-generated.

The odds ratio (OR) in case-control studies can be collapsible or non-collapsible depending on how controls are selected. Sampling methods influence whether the odds ratio reflects the risk ratio or rate ratio, impacting collapsibility.

Keywords:
case-control studiescollapsibilitystudy design

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Last Updated: Jun 1, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Area of Science:

  • Epidemiology
  • Biostatistics
  • Statistical modeling

Background:

  • The odds ratio (OR) is known to be non-collapsible, meaning adjustments for covariates can alter its estimate even without confounding.
  • Effect measures like the risk ratio (RR) are collapsible, while the rate ratio is typically less non-collapsible than the OR.
  • Discussions on non-collapsibility have predominantly focused on cohort studies.

Purpose of the Study:

  • To investigate the concept of non-collapsibility within the context of case-control studies.
  • To examine how different control selection strategies in case-control studies affect the collapsibility of the odds ratio.
  • To determine if the odds ratio in case-control studies inherits collapsibility properties from the underlying cohort study's effect measure.

Main Methods:

  • The study considers a closed cohort with a fixed follow-up time to illustrate non-collapsibility in case-control designs.
  • Compares three control sampling methods: cumulative incidence sampling, case-cohort sampling, and density sampling.
  • Analyzes the collapsibility of the odds ratio estimated by each sampling method in relation to the cohort study's effect measure (OR, RR, or rate ratio).

Main Results:

  • Case-control studies using cumulative incidence sampling estimate the cohort OR and yield a non-collapsible odds ratio.
  • Case-control studies employing case-cohort sampling estimate the cohort RR, resulting in a collapsible odds ratio.
  • Density sampling estimates the cohort rate ratio, producing a case-control odds ratio that is non-collapsible but less so than with cumulative incidence sampling.
  • For rare diseases, all three sampling methods result in approximately collapsible odds ratios.

Conclusions:

  • The collapsibility of the odds ratio in case-control studies is contingent on the chosen control sampling strategy.
  • The odds ratio in case-control studies can be collapsible or non-collapsible, mirroring the properties of the effect measure it is designed to estimate.
  • Understanding these sampling-induced collapsibility differences is crucial for accurate interpretation of odds ratios in case-control research, especially when the disease is rare.