Imagen de Portada

Robust Emax Model Fitting: Addressing Nonignorable Missing Binary Outcome in Dose-Response Analysis

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhang, Jiangshan, Pradhan, Vivek, Zhao, Yuxi
Formato:	Preprint
Publicado:	2024
Materias:	Methodology Applications
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Evaluating Bias Reduction Methods in Binary Emax Model for Reliable Dose-Response Estimation
por: Zhang, Jiangshan, et al.
Publicado: (2025)

Cumulative Logit Ordinal Regression with Proportional Odds under Nonignorable Missing Response -- Application to Phase III Trial
por: Maity, Arnab Kumar, et al.
Publicado: (2025)

Gaussian Copula Models for Nonignorable Missing Data Using Auxiliary Marginal Quantiles
por: Feldman, Joseph, et al.
Publicado: (2024)

Imputation of Nonignorable Missing Data in Surveys Using Auxiliary Margins Via Hot Deck and Sequential Imputation
por: Yang, Yanjiao, et al.
Publicado: (2024)

Maximum Likelihood Estimation under the Emax Model: Existence, Geometry and Efficiency
por: Aletti, Giacomo, et al.
Publicado: (2023)

Causal Inference with Outcomes Truncated by Death and Missing Not at Random
por: Li, Wei, et al.
Publicado: (2024)

Addressing Outcome Reporting Bias in Meta-analysis: A Selection Model Perspective
por: Saracini, Alessandra Gaia, et al.
Publicado: (2024)

Variational Bayesian Multiple Imputation in High-Dimensional Regression Models With Missing Responses
por: Li, Qiushuang, et al.
Publicado: (2025)

Difference-in-differences Design with Outcomes Missing Not at Random
por: Shin, Sooahn
Publicado: (2024)

Outcome-Assisted Multiple Imputation of Missing Treatments
por: Feldman, Joseph, et al.
Publicado: (2025)

Generalizing Trimming Bounds for Endogenously Missing Outcome Data Using Random Forests
por: Samii, Cyrus, et al.
Publicado: (2023)

Latent Moment Models for Recurrent Binary Outcomes: A Bayesian and Quasi-Distributional Approach
por: Ramezani, Niloofar, et al.
Publicado: (2026)

HAL-Based Plug-in Estimation with Pointwise Asymptotic Normality of the Causal Dose-Response Curve
por: Shi, Junming, et al.
Publicado: (2024)

Feasible Dose-Response Curves for Continuous Treatments Under Positivity Violations
por: Bao, Han, et al.
Publicado: (2025)

DEMO: Dose Exploration, Monitoring, and Optimization Using a Biological Mediator for Clinical Outcomes
por: Yang, Cheng-Han, et al.
Publicado: (2024)

Evaluating Binary Outcome Classifiers Estimated from Survey Data
por: Wadekar, Adway S., et al.
Publicado: (2023)

Analysis of Linked Files: A Missing Data Perspective
por: Kamat, Gauri, et al.
Publicado: (2024)

Goodness-of-Fit Checks for Joint Models
por: Rizopoulos, Dimitris, et al.
Publicado: (2026)

Model Selection for Causal Modeling in Missing Exposure Problems
por: Shi, Yuliang, et al.
Publicado: (2024)

A Utility Score Framework for Dose Optimization Studies with Binary Efficacy-Safety Endpoints: Sample Size Determination and Bias Characterization
por: Gu, Xuemin, et al.
Publicado: (2026)

Exact and Conservative Inference for the Average Treatment Effect in Stratified Experiments with Binary Outcomes
por: Li, Jiaxun, et al.
Publicado: (2025)

Estimating Causal Effects for Binary Outcomes Using Per-Decision Inverse Probability Weighting
por: Bao, Yihan, et al.
Publicado: (2023)

Robust and Efficient Estimation in Ordinal Response Models using the Density Power Divergence
por: Pyne, Arijit, et al.
Publicado: (2022)

BOIN Designs for Dose Escalation With Selected Dose Combinations in Oncology Phase I Trials
por: Chen, Yuxuan, et al.
Publicado: (2026)

Residual lifetime prediction for heterogeneous degradation data by Bayesian semi-parametric method
por: Karmakar, Barin, et al.
Publicado: (2025)

Bayesian Bootstrap based Gaussian Copula Model for Mixed Data with High Missing Rates
por: Kim, Seongmin, et al.
Publicado: (2025)

Bayesian Hierarchical Modelling of Noisy Gamma Processes: Model Formulation, Identifiability, Model Fitting, and Extensions to Unit-to-Unit Variability
por: Leadbetter, Ryan, et al.
Publicado: (2024)

Accounting for Missing Data in Public Health Research Using a Synthesis of Statistical and Mathematical Models
por: Zivich, Paul N, et al.
Publicado: (2025)

Modeling Missing at Random Neuropsychological Test Scores Using a Mixture of Binomial Product Experts
por: Suen, Daniel, et al.
Publicado: (2023)

Hybrid Non-informative and Informative Prior Model-assisted Designs for Mid-trial Dose Insertion
por: Yamada, Kana, et al.
Publicado: (2026)

A Seamless Phase II/III Design with Dose Optimization for Oncology Drug Development
por: Li, Yuhan, et al.
Publicado: (2024)

Competing Risk Analysis in Cardiovascular Outcome Trials: A Simulation Comparison of Cox and Fine-Gray Models
por: Wang, Tuo, et al.
Publicado: (2026)

Bayesian reliability acceptance sampling plan sampling plans under adaptive accelerated type-II censored competing risk data
por: Das, Rathin, et al.
Publicado: (2025)

Diagnostics for Regression Models with Semicontinuous Outcomes
por: Yang, Lu
Publicado: (2024)

Establishing the Parallels and Differences Between Right-Censored and Missing Covariates
por: Vazquez, Jesus E., et al.
Publicado: (2024)

A Comparative Evaluation of a Conditional Median-Based Bayesian Growth Curve Modeling Approach with Missing Data
por: Tang, Dandan, et al.
Publicado: (2025)

A Goodness-of-Fit Test for Mixed-Effects Logistic Regression
por: Linden, Ariel
Publicado: (2026)

Robust Estimation of Item Parameters via Divergence Measures in Item Response Theory
por: Itaya, Yuki, et al.
Publicado: (2025)

CUI-MET: Clinical Utility Index Dose Optimization Approach for Multiple-Dose, Multiple-Outcome Randomized Trial Designs
por: Zhang, Fanni, et al.
Publicado: (2025)

Spatially Robust Inference with Predicted and Missing at Random Labels
por: Salerno, Stephen, et al.
Publicado: (2026)