:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Tsvetanova, Antonia, Sperrin, Matthew, Jenkins, David A., Peek, Niels, Buchan, Iain, Hyland, Stephanie, Taylor, Marcus, Wood, Angela, Riley, Richard D., Martin, Glen P.
Format:	Preprint
Publié:	2025
Sujets:	Methodology
Accès en ligne:	https://arxiv.org/abs/2504.06799
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Treatment effect extrapolation in the presence of unmeasured confounding
par: Riley, Stephanie, et autres
Publié: (2025)

A flexible approach to sequential prediction under intervention
par: Sperrin, Matthew, et autres
Publié: (2026)

Scoping review of methodology for aiding generalisability and transportability of clinical prediction models
par: Ploddi, Kritchavat, et autres
Publié: (2024)

Incorporating Missing Data Considerations into Sample Size Calculations for Developing Clinical Prediction Models
par: Martin, Glen P., et autres
Publié: (2026)

Prediction of Survival Outcomes under Clinical Presence Shift: A Joint Neural Network Architecture
par: Jeanselme, Vincent, et autres
Publié: (2025)

Missing Values Handling for Machine Learning Portfolios
par: Chen, Andrew Y., et autres
Publié: (2022)

The risks of risk assessment: causal blind spots when using prediction models for treatment decisions
par: van Geloven, Nan, et autres
Publié: (2024)

Risk-based decision making: estimands for sequential prediction under interventions
par: Luijken, Kim, et autres
Publié: (2023)

Handling Missing Responses under Cluster Dependence with Applications to Language Model Evaluation
par: Zeng, Zhenghao, et autres
Publié: (2025)

Review for Handling Missing Data with special missing mechanism
par: Zhou, Youran, et autres
Publié: (2024)

A Review of Statistical Methods for Handling Nonignorable Missing Data using Instrument Approach
par: Zhao, Yujie
Publié: (2025)

Causal Effect Estimation with TMLE: Handling Missing Data and Near-Violations of Positivity
par: Wiederkehr, Christoph, et autres
Publié: (2025)

Calibration plots for multistate risk prediction models
par: Alexander Pate, et autres
Publié: (2024)

Understanding algorithmic fairness for clinical prediction in terms of subgroup net benefit and health equity
par: Benitez-Aurioles, Jose, et autres
Publié: (2024)

A general sample size framework for developing or updating a clinical prediction model
par: Riley, Richard D, et autres
Publié: (2025)

The Win Ratio at the Design Stage of Clinical Trials
par: Kronthaler, David, et autres
Publié: (2025)

Causal Inference with Missing Exposures and Missing Outcomes
par: Landsiedel, Kirsten E., et autres
Publié: (2025)

Correcting for Missing Data When Evaluating Surrogate Markers in a Clinical Trial
par: Lotspeich, Sarah C., et autres
Publié: (2026)

Joint Models for Handling Non-Ignorable Missing Data using Bayesian Additive Regression Trees: Application to Leaf Photosynthetic Traits Data
par: Goh, Yong Chen, et autres
Publié: (2024)

Borrowing Strength Across Exposures and Outcomes via Index Models for Multi-pollutant Mixtures
par: McGee, Glen, et autres
Publié: (2025)

Estimating Average Causal Effects with Incomplete Exposure and Confounders
par: Wen, Lan, et autres
Publié: (2025)

Extracting useful information about reversible evolutionary processes from irreversible evolutionary accumulation models
par: Johnston, Iain G.
Publié: (2026)

The continuous net benefit: Assessing the clinical utility of prediction models when informing a continuum of decisions
par: Benitez-Aurioles, Jose, et autres
Publié: (2024)

Efficient Difference-in-Differences Estimation when Outcomes are Missing at Random
par: Testa, Lorenzo, et autres
Publié: (2025)

Handling Sparse Non-negative Data in Finance
par: Capponi, Agostino, et autres
Publié: (2025)

A Bayesian location-scale joint model for time-to-event and multivariate longitudinal data with association based on within-individual variability
par: Palma, Marco, et autres
Publié: (2025)

A Multi-Stage Drop-the-Loser Design with Superiority Boundaries
par: Greenstreet, Peter, et autres
Publié: (2026)

Comparison of Parametric versus Machine-learning Multiple Imputation in Clinical Trials with Missing Continuous Outcomes
par: Tackney, Mia S., et autres
Publié: (2025)

Progression to the mean: A practical Bayesian workflow for the development and deployment of clinical prediction models
par: Sadatsafavi, Mohsen, et autres
Publié: (2026)

Cluster weighted models for functional data
par: Anton, Cristina, et autres
Publié: (2025)

Handling cellwise outliers by sparse regression and robust covariance
par: Raymaekers, Jakob, et autres
Publié: (2019)

Predictive Uncertainty Quantification with Missing Covariates
par: Zaffran, Margaux, et autres
Publié: (2024)

Conditional Predictive Inference for Missing Outcomes
par: Lee, Yonghoon, et autres
Publié: (2024)

Imputing Missing Values with External Data
par: Thiesmeier, Robert, et autres
Publié: (2024)

Assessing Sensitivity to IV Exclusion and Exogeneity without First Stage Monotonicity
par: Diegert, Paul, et autres
Publié: (2026)

Handling Missing Data in Probabilistic Regression Trees: Methods and Implementation in R
par: Prass, Taiane Schaedler, et autres
Publié: (2025)

Estimation of Semiparametric Factor Models with Missing Data
par: Zheng, Sijie
Publié: (2025)

Double Robust Weighted Regression with Missing Confounders
par: Bagmar, Md. Shaddam Hossain, et autres
Publié: (2026)

Balancing Weights for Non-monotone Missing Data
par: Dong, Jianing, et autres
Publié: (2024)

Handling outcome-dependent missingness with binary responses: A Heckman-like model
par: Doretti, Marco, et autres
Publié: (2025)