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

Frailty models and rank tests

D Oakes1, J H Jeong

  • 1Department of Statistics, University of Rochester, USA.

Lifetime Data Analysis
|October 27, 1998
PubMed
Summary
This summary is machine-generated.

Omitting covariates in survival analysis can lead to non-proportional hazards, making simple logrank tests suboptimal. Optimal weighted logrank tests, considering frailty distributions, improve efficiency compared to unadjusted tests.

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

A Randomized Phase III Trial of Anthracyclines Followed by Taxane versus Taxane Plus Carboplatin as (Neo)Adjuvant Therapy in Patients with Triple-Negative Breast Cancer: KCSG BR 15-1 PEARLY Trial.

Annals of oncology : official journal of the European Society for Medical Oncology·2026
Same author

Observation of the Singly Cabibbo Suppressed Decay D^{0}→b_{1}(1235)^{-}e^{+}ν_{e} and Evidence for D^{+}→b_{1}(1235)^{0}e^{+}ν_{e}.

Physical review letters·2026
Same author

Genomic and transcriptomic analyses of residual invasive triple-negative breast cancer after neoadjuvant chemotherapy in the prospective MIRINAE trial (a randomized phase II trial of adjuvant atezolizumab plus capecitabine compared to capecitabine; KCSG-BR18-21).

ESMO open·2025
Same author

Precision Measurement of the Branching Fraction of D^{+}→μ^{+}ν_{μ}.

Physical review letters·2025
Same author

Evidence for Two Excited Ω^{-} Hyperons.

Physical review letters·2025
Same author

Observation of D^{+}→η^{'}μ^{+}ν_{μ} and First Experimental Study of D^{+}→η^{'}ℓ^{+}ν_{ℓ} Decay Dynamics.

Physical review letters·2025
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

Area of Science:

  • Survival Analysis
  • Biostatistics
  • Statistical Modeling

Background:

  • Theories of weighted logrank tests and frailty models are connected.
  • Omission of covariates in proportional hazards models can result in non-proportional hazards.
  • This necessitates adjustments to standard statistical tests.

Purpose of the Study:

  • To establish connections between weighted logrank tests and frailty models.
  • To determine optimal weighting functions for omitted covariates.
  • To evaluate the efficiency of various logrank tests under different frailty distributions.

Main Methods:

  • Expressing optimal weighting functions using Laplace transforms of hazard ratios.
  • Analyzing parametric and nonparametric tests.

Related Experiment Videos

  • Extending results to include random censoring.
  • Investigating specific frailty distributions (Gamma, positive stable, inverse Gaussian, displaced Poisson, two-point).

    • Main Results:

    • Loss of efficiency from omitting covariates is generally greater than from misspecifying the hazard model.
    • Optimal tests can be derived based on the distribution of the omitted covariate's hazard ratio.
    • Two-point frailty distributions can be exceptions to the general efficiency loss rule.
    • Random censoring typically increases the efficiency of the simple logrank test relative to the adjusted test.

    Conclusions:

    • Weighted logrank tests offer improved efficiency when covariates are omitted.
    • Frailty models provide a framework for understanding the impact of omitted covariates.
    • Careful consideration of covariate omission and frailty distributions is crucial for accurate survival analysis.