Evidence map›Paper›PMID 40303898›Full record

ArticleBernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability2023

Semiparametric regression of panel count data with informative terminal event.

Xiangbin Hu, L I Liu, Ying Zhang, Xingqiu Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Semiparametric regression of panel count data with informative terminal event.Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability · 2023
    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.

Xiangbin HuDepartment of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China.
L I LiuSchool of Mathematics and Statistics, Wuhan University, Wuhan, China.
Ying ZhangDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, USA.
Xingqiu ZhaoDepartment of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China.

Funding

Tracking and Evaluation CoreU54GM115458 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI RIZZO, MATTHEW · 2016 to 2025
$42.8M
NIGMS NIH HHS U54 GM115458
6 · The paper itself

Abstract

We study a semiparametric model for robust analysis of panel count data with an informative terminal event. To explore the explicit effect of the terminal event on recurrent events of interest, we propose a conditional mean model for a reversed counting process anchoring at the terminal event. Treating the distribution function of the terminal event as a nuisance functional parameter, we develop a predicted least squares-based two-stage estimation procedure with the spline-based sieve estimation technique, and derive the convergence rate of the proposed estimator. Furthermore, overcoming the difficulties caused by the convergence rate slower than

Indexed as

Asymptotic normalitycounting processempirical processpanel count datapredicted least squaresterminal eventtwo-stage estimation

Identifiers

PMID40303898
PMCPMC12040413

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.