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

Two-stage methods for the analysis of pooled data.

T A Stukel1, E Demidenko, J Dykes

  • 1Department of Community and Family Medicine, Section of Biostatistics and Epidemiology, Dartmouth Medical School, Hanover, NH 03755-3863, USA. stukel@darmouth.edu

Statistics in Medicine
|July 6, 2001
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

Making Statistics Clinically Meaningful.

Clinical epidemiology·2026
Same author

Association between Mediterranean diet and metal mixtures concentrations in pregnant people from the New Hampshire Birth Cohort Study.

The Science of the total environment·2023
Same author

RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses.

Epidemics·2022
Same author

Analysis of extracorporeal photopheresis within the frame of the WAA register.

Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis·2021
Same author

Arsenic exposure in relation to apple consumption among infants in the New Hampshire Birth Cohort Study.

Exposure and health·2020
Same author

Specific class of intrapartum antibiotics relates to maturation of the infant gut microbiota: a prospective cohort study.

BJOG : an international journal of obstetrics and gynaecology·2019
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
Same journal

Moving From Individualized Risk-Based Prevention to Benefit-Based Prevention: Estimating Individualized Life-Years Gained From Prevention Services as a Basis for Eligibility.

Statistics in medicine·2026
See all related articles

Pooling data from multiple epidemiologic studies improves accuracy. A two-stage random-effects model offers a practical, unbiased method for analyzing pooled case-control studies, outperforming joint fixed-effects models.

Area of Science:

  • Epidemiology
  • Biostatistics
  • Statistical Modeling

Background:

  • Epidemiologic studies often yield inconclusive results due to small sample sizes or regional variations.
  • Pooling original data from multiple studies can clarify these issues.

Purpose of the Study:

  • To explore the utility of a two-stage random-effects model for analyzing pooled case-control studies.
  • To examine bias in pooled estimators under various conditions.

Main Methods:

  • A two-stage random-effects model was used, analyzing each study with appropriate models and combining results using a linear mixed-effects model.
  • Simulations were conducted to assess bias and standard errors.
  • The model was applied to a case-control study of reproductive history and melanoma risk.

Related Experiment Videos

Main Results:

  • Two-stage methods produced nearly unbiased exposure estimates and standard errors when individual studies were large.
  • Joint fixed-effects logistic regression showed attenuated estimates and underestimated standard errors with heterogeneity.
  • The two-stage model exhibited significantly less bias with interstudy heterogeneity.

Conclusions:

  • The two-stage random-effects model is a simple, valid, and practical method for analyzing pooled binary data.
  • It is advantageous over joint fixed-effects models, especially when covariates are not uniform across studies.
  • This approach enhances the reliability of findings from pooled epidemiologic research.