ArticleBiometrics2019
Confidence bands for multiplicative hazards models: Flexible resampling approaches.
Article in Biometrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Wild bootstrap for counting process-based statistics: a martingale theory-based approach.Lifetime data analysis · 2025Article
- Regression analysis of multiplicative hazards model with time-dependent coefficient for sparse longitudinal covariates.Journal of nonparametric statistics · 2025Article
- Incompletely Observed Nonparametric Factorial Designs With Repeated Measurements: A Wild Bootstrap Approach.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Confidence bands for multiplicative hazards models: Flexible resampling approaches.Biometrics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We propose new resampling-based approaches to construct asymptotically valid time-simultaneous confidence bands for cumulative hazard functions in multistate Cox models. In particular, we exemplify the methodology in detail for the simple Cox model with time-dependent covariates, where the data may be subject to independent right-censoring or left-truncation. We use simulations to investigate their finite sample behavior. Finally, the methods are utilized to analyze two empirical examples with survival and competing risks data.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.