Imagen de Portada

On the limitations for causal inference in Cox models with time-varying treatment

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Knudsen, Mark B., Gabriel, Erin E., Martinussen, Torben, Rytgaard, Helene C. W., Sjölander, Arvid
Formato:	Preprint
Publicado:	2025
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Debiased inference for stochastic treatment interventions with survival outcomes
por: Martinussen, Torben, et al.
Publicado: (2026)

Nonparametric efficient estimation of the longitudinal front-door functional
por: Breum, Marie S., et al.
Publicado: (2025)

The impact of coarsening an exposure on partial identifiability in instrumental variable settings
por: Gabriel, Erin E., et al.
Publicado: (2024)

Causal inference for calibrated scaling interventions on time-to-event processes
por: Rytgaard, Helene Charlotte Wiese, et al.
Publicado: (2025)

Nonparametric efficient causal estimation of the intervention-specific expected number of recurrent events with continuous-time targeted maximum likelihood and highly adaptive lasso estimation
por: Rytgaard, Helene C. W., et al.
Publicado: (2024)

Deriving Complete Constraints in Hidden Variable Models
por: Sachs, Michael C., et al.
Publicado: (2026)

Definition, Identification, and Estimation of the Direct and Indirect Number Needed to Treat
por: Vancak, Valentin, et al.
Publicado: (2025)

Estimation of the Number Needed to Treat, the Number Needed to be Exposed, and the Exposure Impact Number with Instrumental Variables
por: Vancak, Valentin, et al.
Publicado: (2023)

Adding covariates to bounds: What is the question?
por: Jonzon, Gustav, et al.
Publicado: (2025)

Nonparametric Bounds for Evaluating the Clinical Utility of Treatment Rules
por: Hruza, Johannes, et al.
Publicado: (2025)

Variable importance measures for heterogeneous treatment effects with survival outcome
por: Ziersen, Simon Christoffer, et al.
Publicado: (2024)

Causal effect on the number of life years lost due to a specific event: Average treatment effect and variable importance
por: Ziersen, Simon Christoffer, et al.
Publicado: (2025)

Propensity weighting plus adjustment in proportional hazards model is not doubly robust
por: Gabriel, Erin E, et al.
Publicado: (2023)

Efficient nonparametric estimators of discrimination measures with censored survival data
por: Breum, Marie Skov, et al.
Publicado: (2024)

Efficient estimation of the target population average treatment effect from multi-source data
por: Su, Zehao, et al.
Publicado: (2024)

Estimation of treatment effects in presence of differential use of post-randomization concomitant medication with time-to-event outcomes
por: Rytgaard, Helene C. W., et al.
Publicado: (2026)

Nonparametric estimation of the Patient Weighted While-Alive Estimand
por: Ragni, Alessandra, et al.
Publicado: (2024)

Improving precision of cumulative incidence estimates in randomized controlled trials with external controls
por: Su, Zehao, et al.
Publicado: (2025)

Proximal indirect comparison
por: Su, Zehao, et al.
Publicado: (2024)

Prediction meets causal inference: the role of treatment in clinical prediction models
por: van Geloven, Nan, et al.
Publicado: (2020)

Semiparametric fiducial inference for Cox models
por: Cui, Yifan, et al.
Publicado: (2024)

Bounds for causal mediation effects
por: Breum, Marie S., et al.
Publicado: (2025)

Spectral domain likelihoods for Bayesian inference in time-varying parameter models
por: Gustafsson, Oskar, et al.
Publicado: (2024)

Connections as treatment: causal inference with edge interventions in networks
por: Chen, Shuli, et al.
Publicado: (2026)

Bayesian inference on Cox regression models using catalytic prior distributions
por: Li, Weihao, et al.
Publicado: (2023)

A joint QoL-Survival framework with debiased estimation under truncation by death
por: Martinussen, Torben, et al.
Publicado: (2026)

Nonparametric causal inference for optogenetics: sequential excursion effects for dynamic regimes
por: Loewinger, Gabriel, et al.
Publicado: (2024)

Distilling heterogeneous treatment effects: Stable subgroup estimation in causal inference
por: Huang, Melody, et al.
Publicado: (2025)

Dynamic causal inference with time series data
por: Schaffe-Odeleye, Tanique, et al.
Publicado: (2026)

Adaptive sparsening and smoothing of the treatment model for longitudinal causal inference using outcome-adaptive LASSO and marginal fused LASSO
por: Schnitzer, Mireille E, et al.
Publicado: (2024)

Linear models for causal inference under network interference
por: Tong, Eric, et al.
Publicado: (2026)

Credible causal inference beyond toy models
por: Bastías, Pablo Geraldo
Publicado: (2024)

Data collaboration for causal inference from limited medical testing and medication data
por: Nakayama, Tomoru, et al.
Publicado: (2025)

Robust Bayesian causal estimation for causal inference in medical diagnosis
por: Basu, Tathagata, et al.
Publicado: (2024)

Regression-based proximal causal inference for right-censored time-to-event data
por: Li, Kendrick, et al.
Publicado: (2024)

Spatial causal inference in the presence of preferential sampling to study the impacts of marine protected areas
por: Son, Dongjae, et al.
Publicado: (2024)

On robust Bayesian causal inference
por: Alexopoulos, Angelos, et al.
Publicado: (2025)

Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history
por: Seya, Nodoka, et al.
Publicado: (2024)

Identifiable causal inference with noisy treatment and no side information
por: Pöllänen, Antti, et al.
Publicado: (2023)

Conformal causal inference for cluster randomized trials: model-robust inference without asymptotic approximations
por: Wang, Bingkai, et al.
Publicado: (2024)