A note on rank-preserving structural failure time models to account for crossover

The rank-preserving structural failure time model estimators of the acceleration parameter are not based on the joint ranks of the original data, and it is suggested that this makes acceleration-parameter estimator unstable with long-tailed survival distributions.

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Publication Details

Journal
Clinical Trials
Published
2026-01-02
DOI
https://doi.org/10.1177/17407745251405136
Primary Topic
Statistical Methods and Inference
Type
article
Field-Weighted Citation Impact
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article

A note on rank-preserving structural failure time models to account for crossover

E. L. Korn, Jong‐Hyeon Jeong, Boris Freidlin, Pedro A Torres-Saavedra
Clinical Trials
Statistical Methods and Inference
article

A note on rank-preserving structural failure time models to account for crossover

E. L. Korn, Jong‐Hyeon Jeong, Boris Freidlin, Pedro A Torres-Saavedra
article en

Abstract

The rank-preserving structural failure time model estimators of the acceleration parameter are not based on the joint ranks of the original data, and it is suggested that this makes acceleration-parameter estimator unstable with long-tailed survival distributions.

Clinical Trials
National Cancer Institute (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 98%
Statistical Methods and Inference
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A note on rank-preserving structural failure time models to account for crossover — E. L. Korn, Jong‐Hyeon Jeong, et al. · Clinical Trials (2026) | TGRS Research Map | TGRS