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

A generalized estimating equation approach for modeling random length binary vector data

P S Albert1, D A Follmann, H X Barnhart

  • 1Office of Biostatistics Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20892-7938, USA.

Biometrics
|September 18, 1997
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

Cancer mortality and geographic inequalities: a detailed descriptive and spatial analysis of social determinants across US counties, 2018-2021.

Public health·2024
Same author

Estimating gestational age at birth from fundal height and additional anthropometrics: a prospective cohort study.

BJOG : an international journal of obstetrics and gynaecology·2018
Same author

Comparison of methods for identifying small-for-gestational-age infants at risk of perinatal mortality among obese mothers: a hospital-based cohort study.

BJOG : an international journal of obstetrics and gynaecology·2016
Same author

Differences in risk factors for incident and recurrent small-for-gestational-age birthweight: a hospital-based cohort study.

BJOG : an international journal of obstetrics and gynaecology·2014
Same author

Estimation of gene-environment interaction by pooling biospecimens.

Statistics in medicine·2012
Same author

Adiposity and sex hormones across the menstrual cycle: the BioCycle Study.

International journal of obesity (2005)·2012
Same journal

Fast penalized generalized estimating equations for large longitudinal functional datasets.

Biometrics·2026
Same journal

Causally-interpretable random-effects meta-analysis.

Biometrics·2026
Same journal

Statistical inference for mean function of partially observed functional time series.

Biometrics·2026
Same journal

Subgroup identification via Interaction Tree and Mixed Model for Repeated Measures with application to Alzheimer's disease.

Biometrics·2026
Same journal

Finite mixtures of linear quantile regressions with concomitant variables: a solution to endogeneity in longitudinal data modeling.

Biometrics·2026
Same journal

Discussion on "INTACT: a method for integration of longitudinal physical activity data from multiple sources" by Jingru Zhang, Erjia Cui, Hongzhe Li, and Haochang Shou.

Biometrics·2026
See all related articles

This study introduces a new statistical method to analyze both the frequency and severity of health events in clinical trials. This joint modeling approach improves data analysis efficiency for event count and severity data.

Area of Science:

  • Biostatistics
  • Clinical Epidemiology
  • Health Outcomes Research

Background:

  • Clinical trials and epidemiologic studies commonly record event counts (e.g., seizures, hospitalizations).
  • Binary severity measures for these events are often collected but not fully utilized in analyses.
  • Existing methods may not efficiently leverage correlated count and severity data.

Purpose of the Study:

  • To propose a novel methodology for jointly modeling the number of events and their correlated binary severity measures.
  • To develop a flexible statistical framework that accounts for shared covariate effects on both outcomes.
  • To demonstrate the efficiency gains of the proposed joint model over traditional count-only analyses.

Main Methods:

  • Functional linking of regression parameters for count and binary outcome models.

Related Experiment Videos

  • Utilizing a generalized estimating equation (GEE) approach for parameter estimation.
  • Joint modeling of event counts and correlated binary severity data.

    • Main Results:

    • The proposed joint modeling approach offers significant efficiency improvements.
    • Demonstrated gains in statistical power compared to analyzing counts alone.
    • Methodology validated using real-world epilepsy clinical trial data.

    Conclusions:

    • Jointly modeling event counts and severity enhances statistical efficiency in health studies.
    • The proposed methodology provides a robust framework for analyzing complex event data.
    • This approach can lead to more precise estimates and better understanding of disease progression and treatment effects.