Imagen de Portada

Bayesian analysis for pretest-posttest binary outcomes with adaptive significance levels

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Hoyos, Alejandra Estefanía Patiño, Jiménez, Johnatan Cardona
Formato:	Preprint
Publicado:	2024
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Optimal Bayesian stepped-wedge cluster randomised trial designs for binary outcome data
por: Etfer, Laura, et al.
Publicado: (2024)

Bayesian design and analysis of two-arm cluster randomised trials using assurance: extension to binary outcomes and comparison of MCMC and INLA
por: Aloufi, Abdullah, et al.
Publicado: (2025)

A general Bayesian approach to design adaptive clinical trials with time-to-event outcomes
por: McGree, James M., et al.
Publicado: (2023)

Bayesian sequential analysis of adverse events with binary data
por: Wang, Jiayue, et al.
Publicado: (2025)

Constrained Markov decision processes for response-adaptive procedures in clinical trials with binary outcomes
por: Baas, Stef, et al.
Publicado: (2024)

Optimal Bayesian predictive probability for delayed response in single-arm clinical trials with binary efficacy outcome
por: Yoshimoto, Takuya, et al.
Publicado: (2024)

A fully Bayesian approach for the imputation and analysis of derived outcome variables with missingness
por: Campbell, Harlan, et al.
Publicado: (2024)

Fully Bayesian Spectral Clustering and Benchmarking with Uncertainty Quantification for Small Area Estimation
por: Fúquene-Patiño, Jairo
Publicado: (2025)

Extension of W-method and A-learner for multiple binary outcomes
por: Yuki, Shintaro, et al.
Publicado: (2024)

Estimation with missing not at random binary outcomes via exponential tilts
por: Maity, Subha
Publicado: (2025)

Statistical inference for association studies in the presence of binary outcome misclassification
por: Webb, Kimberly A. Hochstedler, et al.
Publicado: (2023)

Bidirectional causal inference for binary outcomes in the presence of unmeasured confounding
por: Deng, Yafang, et al.
Publicado: (2026)

Fast computation of exact confidence intervals for randomized experiments with binary outcomes
por: Aronow, P. M., et al.
Publicado: (2023)

Handling outcome-dependent missingness with binary responses: A Heckman-like model
por: Doretti, Marco, et al.
Publicado: (2025)

The oracle property of the generalized outcome adaptive lasso
por: Baldé, Ismaila
Publicado: (2023)

Bayesian clustering of multiple zero-inflated outcomes
por: Franzolini, Beatrice, et al.
Publicado: (2022)

Meta-analysis and network meta-analysis of time-to-event outcomes with non-proportional hazards: a Bayesian time-varying hazard ratio approach
por: Owen, Rhiannon K, et al.
Publicado: (2026)

Treatment effect estimation under covariate-adaptive randomization with heavy-tailed outcomes
por: Li, Hongzi, et al.
Publicado: (2024)

Revisiting the apparent discrepancy between the frequentist and Bayesian interpretation of an adaptive design
por: Kristensen, Simon Bang, et al.
Publicado: (2025)

Monotone data augmentation algorithm for longitudinal continuous, binary and ordinal outcomes: a unifying approach
por: Tang, Yongqiang
Publicado: (2025)

Data-adaptive gene and pathway-based tests forrare-variant associations with survival outcomes
por: Wang, Yu, et al.
Publicado: (2026)

Optimal estimation for regression discontinuity design with binary outcomes
por: Ishihara, Takuya, et al.
Publicado: (2025)

Testing for causal effect for binary data when propensity scores are estimated through Bayesian Networks
por: Vicard, Paola, et al.
Publicado: (2023)

A comparative study of augmented inverse propensity weighted estimators using outcome-oriented covariate selection via penalization with outcome-adaptive lasso
por: Hongo, Wataru, et al.
Publicado: (2024)

Bayesian adaptive randomization in the I-SPY2 sequential multiple assignment randomized trial
por: Norwood, Peter, et al.
Publicado: (2025)

Bayesian kernel machine regression for heteroscedastic health outcome data
por: Smith, Melissa J., et al.
Publicado: (2025)

Bayesian survival analysis with INLA
por: Alvares, Danilo, et al.
Publicado: (2022)

Meta-analysis of Bayesian analyses
por: Blomstedt, Paul, et al.
Publicado: (2019)

An adaptive enrichment design using Bayesian model averaging for selection and threshold-identification of tailoring variables
por: Maleyeff, Lara, et al.
Publicado: (2024)

Bayesian low-rank latent-cluster regression for mixed health outcomes
por: Huang, Hsin-Hsiung, et al.
Publicado: (2026)

Potential outcome simulation for efficient head-to-head comparison of adaptive dose-finding designs
por: Sweeting, Michael, et al.
Publicado: (2024)

Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
por: Gelman, Andrew, et al.
Publicado: (2019)

Desirability of outcome ranking (DOOR) analysis for multivariate survival outcomes with application to ACTT-1 trial
por: Shu, Shiyu, et al.
Publicado: (2025)

A Bayesian adaptive enrichment design using aggregate historical data to inform individualized treatment recommendations
por: Maleyeff, Lara, et al.
Publicado: (2026)

Bayesian inference for cluster-randomized trials with multivariate outcomes subject to both truncation by death and missingness
por: Tong, Guangyu, et al.
Publicado: (2025)

Ridge, lasso, and elastic-net estimations of the modified Poisson and least-squares regressions for binary outcome data
por: Kitano, Takahiro, et al.
Publicado: (2024)

A Bayesian design for dual-agent dose optimization with targeted therapies
por: Jiménez, José L., et al.
Publicado: (2022)

A fast, flexible simulation framework for Bayesian adaptive designs -- the R package BATSS
por: Couturier, Dominique-Laurent, et al.
Publicado: (2024)

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)

Tail-adaptive Bayesian shrinkage
por: Lee, Se Yoon, et al.
Publicado: (2020)