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 two-sample comparison for multiple ordered event data.

S H Chang1

  • 1Department of Public Health, College of Public Health, National Taiwan University, Taiwan. shuhui@ccms.ntu.edu.tw

Biometrics
|April 28, 2000
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

High Estimated 24-Hour Urinary Sodium Excretion Is Related to Symptomatic Knee Osteoarthritis: A Nationwide Cross-Sectional Population-Based Study.

The journal of nutrition, health & aging·2022
Same author

Determination of maintenance energy requirement and responses of dry ewes to dietary inclusion of lucerne versus concentrate meal.

Animal : an international journal of animal bioscience·2021
Same author

Diagnosing syndesmotic instability with dynamic ultrasound - establishing the natural variations in normal motion.

Injury·2020
Same author

Unusual presentations of lymphocytic phlebitis of the digestive tract.

Pathology·2015
Same author

The association of radiographic progression with serum R-spondin 1 (RSPO1) levels or Dickkopf-1 (DKK1)/RSPO1 ratios in rheumatoid arthritis patients: clinical evidence for reciprocal inhibition between DKK1 and RSPO1.

Scandinavian journal of rheumatology·2014
Same author

Dynamic layer rearrangement during growth of layered oxide films by molecular beam epitaxy.

Nature materials·2014
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 novel methods for analyzing disease progression by examining sojourn times between events. The research develops robust statistical approaches for handling dependent censoring in longitudinal studies, offering consistent estimators for group effects.

Area of Science:

  • Biostatistics
  • Epidemiology
  • Longitudinal Data Analysis

Background:

  • Disease progression is often characterized by a sequence of ordered events.
  • Understanding sojourn times between these events is crucial for disease management.
  • Existing methods may struggle with dependent censoring in multivariate event data.

Purpose of the Study:

  • To develop statistical methods for analyzing disease progression using sojourn times between ordered events.
  • To compare disease processes between two groups using a semiparametric accelerated failure time model.
  • To address challenges posed by dependent censoring in longitudinal studies.

Main Methods:

  • Utilized a semiparametric accelerated failure time model to parameterize group effects on sojourn times.

Related Experiment Videos

  • Developed a log-rank-type estimating approach for dependent censoring by rescaling times.
  • Generated pseudo-censoring times for independent censoring scenarios to obtain unbiased estimating functions.

    • Main Results:

    • The proposed log-rank-type estimator is consistent and asymptotically normal for group effects under dependent censoring.
    • The method effectively handles unspecified dependence structures among multivariate sojourn times.
    • Simulation studies and a real-world application demonstrate the utility of the proposed methods.

    Conclusions:

    • The developed methods provide a robust framework for analyzing disease progression with ordered events and dependent censoring.
    • The approach allows for reliable estimation of group effects in longitudinal studies.
    • This work offers valuable tools for epidemiological and biostatistical research on disease processes.