Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Analysis of case-crossover designs

R J Marshall1, R T Jackson

  • 1Department of Community Health, University of Auckland, New Zealand.

Statistics in Medicine
|December 30, 1993
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Systematic review of the prevalence of faecal incontinence.

The British journal of surgery·2016
Same author

Putting it bluntly: communication skills in the Iliad.

Medical humanities·2013
Same author

Mortality risk stratification in severely anaemic Jehovah's Witness patients.

Internal medicine journal·2012
Same author

Clinical benefits and cost-effectiveness of allogeneic red-blood-cell transfusion in severe symptomatic anaemia.

Vox sanguinis·2011
Same author

Determining levels of fecal incontinence in the community: a New Zealand cross-sectional study.

Diseases of the colon and rectum·2011
Same author

Complicated hyperthyroidism.

Bulletin of the University of Minnesota Hospitals and Minnesota Medical Foundation. University of Minnesota. Hospitals·2010
Same journal

Latent Class Log-Linear Models for Estimating Diagnostic Test Accuracy Without a Gold Standard: A Simulation Study.

Statistics in medicine·2026
Same journal

Interpretable Bayesian Modeling for Multireader Multicase Studies: Addressing Overdispersion and Limited Sample Size in Diagnostic Enhancement Evaluation.

Statistics in medicine·2026
Same journal

Adaptive Sequential Multiple Hypotheses Testing for Concomitant Vaccine Safety Surveillance.

Statistics in medicine·2026
Same journal

Novel Distance Regression for Repeated Outcomes With Missing Data: Applications to Longitudinal and Crossover Studies of Microbiome Beta-Diversity.

Statistics in medicine·2026
Same journal

Optimal Weighted Tests for Replication Studies and the 'Two-Trials Rule' With Multiple Hypotheses.

Statistics in medicine·2026
Same journal

Identifiable Copula-Double-Cox Models: A Fully Parametric Framework for Dependent Right-Censored Survival Data.

Statistics in medicine·2026
See all related articles

The case-crossover design analyzes transient exposures and acute illness risk. Maximum likelihood analysis offers a general method for these studies, applicable to alcohol consumption and heart attack risk.

Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Case-crossover designs are valuable for studying transient exposures and acute illness risk.
  • This design uses cases as their own controls, comparing exposure at the event time to usual behavior.
  • Existing methods like Mantel-Haenszel offer an approach, but maximum likelihood provides a more general solution.

Purpose of the Study:

  • To present a maximum likelihood method for analyzing case-crossover study designs.
  • To demonstrate the generalizability of this method for multiple transient exposures.
  • To address the practical challenge of estimating usual behavior in case-crossover studies.

Main Methods:

  • Maximum likelihood estimation is proposed for analyzing case-crossover data.
  • The Mantel-Haenszel method is identified as an approximate solution for binary exposures.

Related Experiment Videos

  • The study highlights the importance of careful questionnaire design for capturing usual behavior.

    • Main Results:

    • Maximum likelihood analysis is shown to be a general method for case-crossover designs.
    • The Mantel-Haenszel approach is an approximation to the likelihood equations for binary exposures.
    • Estimating usual behavior requires in-depth questioning and careful questionnaire design.

    Conclusions:

    • Maximum likelihood analysis provides a robust framework for case-crossover studies.
    • Accurate estimation of usual behavior is crucial for the validity of case-crossover designs.
    • The method is illustrated with an analysis of alcohol consumption and myocardial infarction risk.