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

Comparing sub-survival functions in a competing risks model.

K C Carriere1, S C Kochar

  • 1Department of Mathematical Sciences, University of Alberta, Edmonton. kc.carriere@ualberta.ca

Lifetime Data Analysis
|April 14, 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

Extended Clopidogrel Therapy Beyond 12 Months and Long-Term Outcomes in Patients With Diabetes Mellitus Receiving Coronary Arterial Second-Generation Drug-Eluting Stents.

The American journal of cardiology·2018
Same author

Off-Pump Coronary Artery Bypass Graft Versus Drug-Eluting Stent Implantation in Patients with Multivessel Disease Involving the Right Coronary Artery.

The Thoracic and cardiovascular surgeon·2018
Same author

Impact of different nitrate therapies on long-term clinical outcomes of patients with vasospastic angina: A propensity score-matched analysis.

International journal of cardiology·2017
Same author

Detecting and correcting for publication bias in meta-analysis - A truncated normal distribution approach.

Statistical methods in medical research·2016
Same author

Comorbidity as a contributor to frequent severe acute exacerbation in COPD patients.

International journal of chronic obstructive pulmonary disease·2016
Same author

Clinical implications of low-dose aspirin on vasospastic angina patients without significant coronary artery stenosis; a propensity score-matched analysis.

International journal of cardiology·2016
Same journal

Shared frailty sieve estimation for dependent left truncated and interval censored data.

Lifetime data analysis·2026
Same journal

Functional win-fractions regression models for composite outcomes.

Lifetime data analysis·2026
Same journal

Variable selection in causal semiparametric transformation models with all-or-nothing treatment compliance.

Lifetime data analysis·2026
Same journal

Correction to: A uniformisation-driven algorithm for inference-related estimation of a phase-type ageing model.

Lifetime data analysis·2026
Same journal

Unobserved heterogeneity in threshold regression based on the hitting times of a reflected Brownian motion for recurrent hypoglycemia.

Lifetime data analysis·2026
Same journal

Variable selection with broken adaptive ridge regression for interval-censored competing risks data.

Lifetime data analysis·2026
See all related articles

This study introduces new statistical tests for comparing competing risks using sub-survival functions. These tests offer a more direct interpretation than existing methods based on cumulative incidence functions.

Area of Science:

  • Statistics
  • Survival Analysis
  • Competing Risks

Background:

  • Traditional competing risks analysis often compares risk equality or severity.
  • Existing methods primarily rely on hazard rates and cumulative incidence functions.

Purpose of the Study:

  • To propose novel statistical tests for comparing two competing risks.
  • To evaluate these tests against an ordered alternative using sub-survival functions.

Main Methods:

  • Development of Kolmogorov-Smirnov type tests.
  • Focus on maximum differences between sub-survival functions.

Main Results:

  • Proposed tests are extensions of existing methods.
  • Simulation studies show competitive performance against cumulative incidence function-based tests.

Related Experiment Videos

  • New tests offer more direct interpretation of results.

    • Conclusions:

    • The proposed sub-survival function tests are effective and interpretable.
    • These new tests provide a valuable alternative in competing risks analysis.