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

Robustness of the latent variable model for correlated binary data.

M Tan1, Y Qu, J S Rao

  • 1Department of Biostatistics and Epidemiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA. ming.tan@stjude.org

Biometrics
|April 25, 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

Effect of Orem-based Nursing Intervention with Mobile Application on the Symptoms, Quality of Life, and Self-Care Abilities of Gastrointestinal Cancer Patients; A Quasi-Experimental Study.

Nigerian journal of clinical practice·2026
Same author

Beyond the surface: a case report of penile tuberculosis as the first sign of miliary disease in a solid organ transplant recipient.

ASM case reports·2026
Same author

A Prospective, Randomised Controlled Trial Comparing the use of the Proximal Femoral Nail - Antirotation and Dynamic Hip Screw for Stable Intertrochanteric Femur Fractures-Stable Trochanteric Fractures Intramedullary versus Extramedullary (STRIVE) Study.

Malaysian orthopaedic journal·2025
Same author

Retraction Note to: Adenovirus-mediated transfer of siRNA against MMP-2 mRNA results in impaired invasion and tumor-induced angiogenesis, induces apoptosis in vitro and inhibits tumor growth in vivo in glioblastoma.

Oncogene·2025
Same author

[Treatment of pharyngeal and esophageal extraluminal foreign bodies with lateral cervical incision in 7 cases].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2024
Same author

Drought priming-induced stress memory improves subsequent drought or heat tolerance via activation of γ-aminobutyric acid-regulated pathways in creeping bentgrass.

Plant biology (Stuttgart, Germany)·2024
Same journal

Interim analysis in sequential multiple assignment randomized trials for survival outcomes.

Biometrics·2026
Same journal

Acknowledgment of Referees 2025.

Biometrics·2026
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
See all related articles

Marginal regression models for binary data are robust. Parameter estimates remain reliable even with different latent distributions, including skewed ones, enhancing their applicability in statistical analysis.

Area of Science:

  • Statistics
  • Biostatistics

Background:

  • Conditional approaches directly model binary data.
  • Parametric marginal regression models assume an underlying multivariate normal vector for correlated binary outcomes.
  • Existing models offer flexibility in correlation structures but raise questions about robustness to latent distribution choices.

Purpose of the Study:

  • To assess the robustness of parameter estimates in marginal regression models for correlated binary data with respect to the choice of latent distribution.
  • To extend latent modeling to include multivariate t-distributed latent vectors.
  • To investigate the robustness of parameter estimates when the latent distribution is skewed.

Main Methods:

  • Extended latent marginal regression modeling to incorporate multivariate t-distributed latent vectors.

Related Experiment Videos

  • Conducted simulation studies to evaluate parameter estimate robustness.
  • Utilized an iterative algorithm to demonstrate robustness concerning covariance structure misspecifications.

    • Main Results:

    • Parameter estimates demonstrated robustness with respect to the latent distribution, even when skewed.
    • The study provides empirical evidence of robustness across different latent distributions.
    • Robustness of regression coefficients to covariance misspecifications implies robustness to latent vector distributional assumptions.

    Conclusions:

    • Marginal regression models exhibit robustness in parameter estimates concerning the latent distribution.
    • The findings support the reliability of these models even with misspecified latent distributions.
    • This robustness extends to the underlying distributional assumptions of the latent vector.