Evidence map›Paper›PMID 42045605›Full record

ArticleLifetime data analysis2026

A dependent and censored first hitting-time model with compound Poisson processes.

Mikael Escobar-Bach, Alexandre Popier, Malo Sahin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Lifetime data analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mikael Escobar-BachLAREMA, Université d'Angers, 2 bd de Lavoisier, 49000, Angers, France. mikael.escobar-bach@univ-angers.fr.ORCID http://orcid.org/0000-0003-2158-3068
Alexandre PopierLaboratoire Manceau de Mathématiques, Le Mans Université, Avenue Olivier Messiaen, 72085, Le Mans, France.
Malo SahinLAREMA, Université d'Angers, 2 bd de Lavoisier, 49000, Angers, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We consider a bivariate first hitting-time model in which durations are the crossing times of dependent compound Poisson processes with fixed thresholds. The identifiability of the model is discussed, and likelihood estimators of the model parameters are proposed. We obtain the asymptotic properties of the estimators and underline their finite sample performance with a simulation study on synthetic data. The practical applicability of our approach is demonstrated by an application using data from patients suffering from mushroom poisoning.

Indexed as

Models, StatisticalComputer SimulationHumansLikelihood FunctionsMushroom PoisoningPoisson DistributionSurvival AnalysisCompound Poisson processDependent censoringFirst hitting-time modelSurvival analysis

Identifiers

PMID42045605
PMCPMC13121319

What OpenQuestion holds

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Registered trials

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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.