Cover Image

Optimizing precision in stepped-wedge designs via machine learning and quadratic inference functions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lyu, Liangbo, Wang, Bingkai
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

How to achieve model-robust inference in stepped wedge trials with model-based methods?
by: Wang, Bingkai, et al.
Published: (2024)

Model-robust standardization in stepped wedge designs
by: Fang, Xi, et al.
Published: (2025)

Asymptotic inference with flexible covariate adjustment under rerandomization and stratified rerandomization
by: Wang, Bingkai, et al.
Published: (2024)

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

Randomization inference for stepped-wedge designs with noncompliance with application to a palliative care pragmatic trial
by: Zhang, Jeffrey, et al.
Published: (2025)

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

Handling incomplete outcomes and covariates in cluster-randomized trials: doubly-robust estimation, efficiency considerations, and sensitivity analysis
by: Wang, Bingkai, et al.
Published: (2024)

Can discrete-time analyses be trusted for stepped wedge trials with continuous recruitment?
by: Wang, Hao, et al.
Published: (2025)

Maintaining the validity of inference from linear mixed models in stepped-wedge cluster randomized trials under misspecified random-effects structures
by: Ouyang, Yongdong, et al.
Published: (2023)

Assessing mediation in cross-sectional stepped wedge cluster randomized trials
by: Cao, Zhiqiang, et al.
Published: (2024)

Design-based edge-level causal inference with machine learning assisted covariate adjustment
by: Yu, Haoyang, et al.
Published: (2026)

Analysis of cohort stepped wedge cluster-randomized trials with non-ignorable dropout via joint modeling
by: Gasparini, Alessandro, et al.
Published: (2024)

Online conformal inference for multi-step time series forecasting
by: Wang, Xiaoqian, et al.
Published: (2024)

Time-varying treatment effect models in stepped-wedge cluster-randomized trials with multiple interventions
by: Chen, Zhe, et al.
Published: (2025)

Factors affecting power in stepped wedge trials when the treatment effect varies with time
by: Kenny, Avi, et al.
Published: (2025)

Model-assisted analysis of covariance estimators for stepped wedge cluster randomized experiments
by: Chen, Xinyuan, et al.
Published: (2023)

Comment on "Generic machine learning inference on heterogeneous treatment effects in randomized experiments."
by: Imai, Kosuke, et al.
Published: (2025)

A Differential Effect Approach to Partial Identification of Treatment Effects
by: Chen, Kan, et al.
Published: (2023)

Estimands and doubly robust estimation for cluster-randomized trials with survival outcomes
by: Fang, Xi, et al.
Published: (2025)

Analysis of stepped wedge cluster randomized trials in the presence of a time-varying treatment effect
by: Kenny, Avi, et al.
Published: (2021)

Test-negative designs with various reasons for testing: statistical bias and solution
by: Yu, Mengxin, et al.
Published: (2023)

Power calculation for cross-sectional stepped wedge cluster randomized trials with a time-to-event endpoint
by: Baumann, Mary Ryan, et al.
Published: (2023)

A step towards the integration of machine learning and classic model-based survey methods
by: Żądło, Tomasz, et al.
Published: (2024)

Cluster randomized trials designed to support generalizable inferences
by: Robertson, Sarah E., et al.
Published: (2022)

More power to you: Using machine learning to augment human coding for more efficient inference in text-based randomized trials
by: Mozer, Reagan, et al.
Published: (2023)

A sensitivity analysis approach to principal stratification with a continuous longitudinal intermediate outcome: Applications to a cohort stepped wedge trial
by: Yang, Lei, et al.
Published: (2024)

Two-step semiparametric empirical likelihood inference from capture-recapture data with missing covariates
by: Liu, Yang, et al.
Published: (2025)

Doubly robust estimators of the restricted mean time in favor estimands in individual- and cluster-randomized trials
by: Fang, Xi, et al.
Published: (2026)

Non-parametric Bayesian inference via loss functions under model misspecification
by: Luo, Yu, et al.
Published: (2021)

Improved inference for nonparametric regression and regression-discontinuity designs
by: Cavaliere, Giuseppe, et al.
Published: (2025)

Model-robust standardization in cluster-randomized trials
by: Li, Fan, et al.
Published: (2025)

Principled analysis of crossover designs: causal effects, efficient estimation, and robust inference
by: Jiang, Zhichao, et al.
Published: (2025)

Causal inference with a functional outcome
by: Ecker, Kreske, et al.
Published: (2023)

Bayesian inference for functional extreme events defined via partially unobserved processes
by: Thannheimer, Max, et al.
Published: (2025)

Bayesian inference for the learning rate in Generalised Bayesian inference
by: Lee, Jeong Eun, et al.
Published: (2025)

Effective and flexible depth-based inference for functional parameters
by: Yeon, Hyemin
Published: (2026)

Change point localisation and inference in fragmented functional data
by: Xue, Gengyu, et al.
Published: (2024)

CoMMiT: Co-informed inference of microbiome-metabolome interactions via transfer learning
by: Li, Leiyue, et al.
Published: (2025)

Online robust estimation and bootstrap inference for function-on-scalar regression
by: Cheng, Guanghui, et al.
Published: (2024)

Adaptive weighted approach for high-dimensional statistical learning and inference
by: Lu, Jun, et al.
Published: (2022)