Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Wang, Bingkai"'
Autor:
Wang, Bingkai, Li, Fan
Rerandomization is an effective treatment allocation procedure to control for baseline covariate imbalance. For estimating the average treatment effect, rerandomization has been previously shown to improve the precision of the unadjusted and the line
Externí odkaz:
http://arxiv.org/abs/2406.02834
A stepped wedge design is a unidirectional crossover design where clusters are randomized to distinct treatment sequences. While model-based analysis of stepped wedge designs is standard practice to evaluate treatment effects accounting for clusterin
Externí odkaz:
http://arxiv.org/abs/2401.15680
In cluster-randomized trials (CRTs), missing data can occur in various ways, including missing values in outcomes and baseline covariates at the individual or cluster level, or completely missing information for non-participants. Among the various ty
Externí odkaz:
http://arxiv.org/abs/2401.11278
Traditional statistical inference in cluster randomized trials typically invokes the asymptotic theory that requires the number of clusters to approach infinity. In this article, we propose an alternative conformal causal inference framework for anal
Externí odkaz:
http://arxiv.org/abs/2401.01977
Autor:
Yu, Mengxin, Li, Kendrick Qijun, Jewell, Nicholas, Tchetgen, Eric Tchetgen, Small, Dylan, Shi, Xu, Wang, Bingkai
Test-negative designs are widely used for post-market evaluation of vaccine effectiveness, particularly in cases where randomization is not feasible. Differing from classical test-negative designs where only healthcare-seekers with symptoms are inclu
Externí odkaz:
http://arxiv.org/abs/2312.03967
We consider identification and inference for the average treatment effect and heterogeneous treatment effect conditional on observable covariates in the presence of unmeasured confounding. Since point identification of these treatment effects is not
Externí odkaz:
http://arxiv.org/abs/2303.06332
Cluster-randomized experiments are increasingly used to evaluate interventions in routine practice conditions, and researchers often adopt model-based methods with covariate adjustment in the statistical analyses. However, the validity of model-based
Externí odkaz:
http://arxiv.org/abs/2210.07324
In 2019, the World Health Organization identified dengue as one of the top ten global health threats. For the control of dengue, the Applying Wolbachia to Eliminate Dengue (AWED) study group conducted a cluster-randomized trial in Yogyakarta, Indones
Externí odkaz:
http://arxiv.org/abs/2202.03379
Publikováno v:
In Food Chemistry 1 October 2024 454
In the analyses of cluster-randomized trials, mixed-model analysis of covariance (ANCOVA) is a standard approach for covariate adjustment and handling within-cluster correlations. However, when the normality, linearity, or the random-intercept assump
Externí odkaz:
http://arxiv.org/abs/2112.00832