Evidence map›Paper›PMID 25663727›Full record

ArticleJournal of the American Statistical Association2014

Score Estimating Equations from Embedded Likelihood Functions under Accelerated Failure Time Model.

Jing Ning, Jing Qin, Yu Shen

Abstract read
In one paragraph

Article in Journal of the American Statistical Association, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Limitations of the cox proportional hazards model and alternative approaches in metachronous recurrence research.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Semiparametric Model for Bivariate Survival Data Subject to Biased Sampling.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2019
    Article
  10. Missing Information Principle: A Unified Approach for General Truncated and Censored Survival Data Problems.Statistical science : a review journal of the Institute of Mathematical Statistics · 2018
    Article
  11. Article
  12. Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jing NingDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.
Jing QinBiostatistics Research Branch, National Institute of Allergy and Infectious Diseases, NIH Bethesda, Maryland 20892, USA.
Yu ShenDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
STATISTICAL METHODS FOR BREAST CANCER SCREENING STUDIESR01CA079466 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SHEN, YU · 1999 to 2014
$1.5M
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA079466
6 · The paper itself

Abstract

The semiparametric accelerated failure time (AFT) model is one of the most popular models for analyzing time-to-event outcomes. One appealing feature of the AFT model is that the observed failure time data can be transformed to identically independent distributed random variables without covariate effects. We describe a class of estimating equations based on the score functions for the transformed data, which are derived from the full likelihood function under commonly used semiparametric models such as the proportional hazards or proportional odds model. The methods of estimating regression parameters under the AFT model can be applied to traditional right-censored survival data as well as more complex time-to-event data subject to length-biased sampling. We establish the asymptotic properties and evaluate the small sample performance of the proposed estimators. We illustrate the proposed methods through applications in two examples.

Indexed as

Accelerated failure time modelCox modelLength-biased dataLikelihood functionProportional odds modelScore equation

Identifiers

PMID25663727
PMCPMC4317328

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.