Evidence map›Paper›PMID 37790796›Full record

ArticleBiometrika2022

Statistical inference on shape and size indexes for counting processes.

Yifei Sun, Sy Han Chiou, Kieren A Marr, Chiung-Yu Huang

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrika, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 35% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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

4 authors at 4 institutions in 1 country.

Yifei SunDepartment of Biostatistics, Columbia University Mailman School of Public Health, 722 W168th St., New York, New York 10032, U.S.A.
Sy Han ChiouDepartment of Mathematical Sciences, University of Texas at Dallas, 800 W. Campbell Road, Richardson, Texas 75080, U.S.A.
Kieren A MarrJohns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, Maryland 21205, U.S.A.
Chiung-Yu HuangDepartment of Epidemiology & Biostatistics, University of California, 550 16th St., San Francisco, California 94158, U.S.A.
Columbia University · USJohns Hopkins University · USThe University of Texas at Dallas · USUniversity of California, San Francisco · US

Funding

Statistical Methods for Survival and Recurrent Event Data in Clinical ResearchR01CA193888 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HUANG, CHIUNG-YU · 2015 to 2019
$1.7M
Patient Oriented Research in Transplant and Oncology IDK24AI085118 · NIAID · JOHNS HOPKINS UNIVERSITY · PI MARR, KIEREN A. · 2010 to 2014
$995k
NCI NIH HHS R01 CA193888NIAID NIH HHS K24 AI085118
6 · The paper itself

Abstract

Single-index models have gained increased popularity in time-to-event analysis owing to their model flexibility and advantage in dimension reduction. We propose a semiparametric framework for the rate function of a recurrent event counting process by modelling its size and shape components with single-index models. With additional monotone constraints on the two link functions for the size and shape components, the proposed model possesses the desired directional interpretability of covariate effects and encompasses many commonly used models as special cases. To tackle the analytical challenges arising from leaving the two link functions unspecified, we develop a two-step rank-based estimation procedure to estimate the regression parameters with or without informative censoring. The proposed estimators are asymptotically normal, with a root-

Indexed as

Dimension reductionInformative censoringKernel smoothingRate functionRecurrent event

Identifiers

PMID37790796
PMCPMC10546871
OpenAlexW3129978918

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.