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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Identification of the miRNA-mRNA regulatory network in multiple sclerosis.

Neurological research·2016
Same author

Long non-coding RNA PVT1 promotes osteosarcoma development by acting as a molecular sponge to regulate miR-195.

Oncotarget·2016
Same author

Fluorescent Nanocomposite for Visualizing Cross-Talk between MicroRNA-21 and Hydrogen Peroxide in Ischemia-Reperfusion Injury in Live Cells and In Vivo.

Analytical chemistry·2016
Same author

Propensity Score Methods in Nursing Research: Take Advantage of Them but Proceed With Caution.

Nursing research·2016
Same author

Optical Fiber Temperature and Torsion Sensor Based on Lyot-Sagnac Interferometer.

Sensors (Basel, Switzerland)·2016
Same author

Silica dioxide nanoparticles combined with cold exposure induce stronger systemic inflammatory response.

Environmental science and pollution research international·2016
Same journal

A Bayesian functional concurrent zero-inflated Dirichlet-multinomial regression model with application to infant microbiome.

Biostatistics (Oxford, England)·2026
Same journal

Towards optimal environmental policies: policy learning under arbitrary bipartite network interference.

Biostatistics (Oxford, England)·2026
Same journal

Multilevel functional quantile principal component analysis.

Biostatistics (Oxford, England)·2026
Same journal

Adaptive transfer learning for time-to-event modeling with applications in disease risk assessment.

Biostatistics (Oxford, England)·2026
Same journal

High-dimensional test for one-sided hypotheses.

Biostatistics (Oxford, England)·2026
Same journal

NBSR: a Negative Binomial Softmax Regression model for microRNA-seq data analysis.

Biostatistics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jan 8, 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

2.5K

Application of conditional moment tests to model checking for generalized linear models.

Wei Pan1

  • 1A460 Mayo Building, MMC 303, Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA. weip@biostat.umn.edu

Biostatistics (Oxford, England)
|August 23, 2003
PubMed
Summary
This summary is machine-generated.

Conditional moment tests (CMTs) offer effective model checking for generalized estimation equation (GEE) analyses with correlated discrete data. This study demonstrates their utility in marginal logistic regression, providing valuable diagnostic tools for complex statistical modeling.

More Related Videos

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.7K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.2K

Related Experiment Videos

Last Updated: Jan 8, 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

2.5K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.7K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.2K

Area of Science:

  • Statistical modeling
  • Econometrics
  • Biostatistics

Background:

  • Generalized linear models (GLMs) are widely used but pose challenges for model checking, especially with correlated discrete response data.
  • Existing methods for model checking in generalized estimation equation (GEE) analyses are limited, necessitating new approaches.

Purpose of the Study:

  • To illustrate the flexibility and effectiveness of conditional moment tests (CMTs) for model checking in GEE analyses.
  • To apply CMTs to a real-world case study involving marginal logistic regression.

Main Methods:

  • Application of conditional moment tests (CMTs) for diagnostic checking in generalized estimation equation (GEE) models.
  • Utilized graphical methods alongside CMTs for comprehensive model evaluation.
  • Case study focused on marginal logistic regression with a real dataset.

Main Results:

  • Conditional moment tests (CMTs) demonstrated significant flexibility and effectiveness in checking generalized linear models (GLMs) within GEE analyses.
  • CMTs encompass various existing diagnostic tests, including score tests for omitted covariates, as special cases.

Conclusions:

  • Conditional moment tests (CMTs) represent a valuable addition to the toolkit for model checking in generalized estimation equation (GEE) analyses.
  • The study highlights CMTs as powerful and versatile diagnostic tools for complex statistical modeling scenarios.