Evidence map›Paper›PMID 39648874›Full record

ArticleStatistics in medicine2025

Smooth Hazards With Multiple Time Scales.

Angela Carollo, Paul Eilers, Hein Putter, Jutta Gampe

Abstract read
In one paragraph

Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Competing risks models with two time scales.Statistical methods in medical research · 2025
    Article
  3. 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.

Angela CarolloMax Planck Institute for Demographic Research, Rostock, Germany.ORCID 0000-0002-5625-6553
Paul EilersErasmus University Medical Center, Rotterdam, The Netherlands.
Hein PutterDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.ORCID 0000-0001-5395-1422
Jutta GampeMax Planck Institute for Demographic Research, Rostock, Germany.ORCID 0000-0001-8189-2853

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hazard models are the most commonly used tool to analyze time-to-event data. If more than one time scale is relevant for the event under study, models are required that can incorporate the dependence of a hazard along two (or more) time scales. Such models should be flexible to capture the joint influence of several time scales, and nonparametric smoothing techniques are obvious candidates.

Indexed as

AlgorithmsProportional Hazards ModelsComputer SimulationHumansLikelihood FunctionsModels, StatisticalPoisson DistributionTime FactorsGLAM algorithmsmultidimensional hazardsparse mixed modeltime scales

Identifiers

PMID39648874
PMCPMC11701971

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.