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A practical limitation of cluster randomized controlled trials (cRCTs) is that the number of available clusters may be small, resulting in an increased risk of baseline imbalance under simple randomization. Constrained randomization…

统计方法学 · 统计学 2022-01-19 Yunji Zhou , Elizabeth L. Turner , Ryan A. Simmons , Fan Li

Sequential, multiple assignment randomized trials (SMARTs), which assist in the optimization of adaptive interventions, are growing in popularity in education and behavioral sciences. This is unsurprising, as adaptive interventions reflect…

统计方法学 · 统计学 2023-09-26 Timothy Lycurgus , Amy Kilbourne , Daniel Almirall

Personalized medicine seeks to identify the causal effect of treatment for a particular patient as opposed to a clinical population at large. Most investigators estimate such personalized treatment effects by regressing the outcome of a…

机器学习 · 统计学 2021-09-02 Eric V. Strobl , Shyam Visweswaran

Sequential, multiple assignment, randomized trial (SMART) designs have become increasingly popular in the field of precision medicine by providing a means for comparing sequences of treatments tailored to the individual patient, i.e.,…

应用统计 · 统计学 2018-04-13 William J. Artman , Inbal Nahum-Shani , Tianshuang Wu , James R. McKay , Ashkan Ertefaie

Analyses of cluster randomized trials (CRTs) can be complicated by informative missing outcome data. Methods such as inverse probability weighted generalized estimating equations have been proposed to account for informative missingness by…

统计方法学 · 统计学 2023-04-13 Chia-Rui Chang , Rui Wang

Educational research often studies subjects that are in naturally clustered groups of classrooms or schools. When designing a randomized experiment to evaluate an intervention directed at teachers, but with effects on teachers and their…

应用统计 · 统计学 2009-08-17 Brenda Jenney , Sharon Lohr

Randomized Controlled Trials (RCTs) are the gold standard for comparing the effectiveness of a new treatment to the current one (the control). Most RCTs allocate the patients to the treatment group and the control group by uniform…

机器学习 · 统计学 2018-10-22 Onur Atan , William R. Zame , Mihaela van der Schaar

The Stepped Wedge Design (SWD) is a form of cluster randomized trial, usually comparing two treatments, which is divided into time periods and sequences, with clusters allocated to sequences. Typically all sequences start with the standard…

统计方法学 · 统计学 2020-11-06 John N. S. Matthews

Dynamic treatment regimes (DTRs) are sequences of decision rules to guide treatment assignments in response to a patient's evolving, time-varying disease status. Sequential multiple assignment randomized trials (SMARTs) are considered the…

统计方法学 · 统计学 2026-04-29 Xinru Wang , Meghna Bose , Bibhas Chakraborty , Robert Mahar

Dynamic treatment regimes (DTRs) are used in medicine to tailor sequential treatment decisions to patients by considering patient heterogeneity. Common methods for learning optimal DTRs, however, have shortcomings: they are typically based…

机器学习 · 统计学 2023-06-21 Theresa Blümlein , Joel Persson , Stefan Feuerriegel

Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each stage by potentially time-varying patient features and intermediate outcomes observed in previous stages. The complexity, patient heterogeneity and chronicity…

统计方法学 · 统计学 2016-11-09 Ying Liu , Yuanjia Wang , Michael R. Kosorok , Yingqi Zhao , Donglin Zeng

Both cluster randomized trials and quasi-experimental designs are used to evaluate the impact of health and social policies and interventions. Stepped-wedge cluster randomized trials randomize a staggered adoption approach, while recent…

统计方法学 · 统计学 2026-04-15 Haidong Lu , Gregg S. Gonsalves , Fan Li , Guanyu Tong , Lee Kennedy-Shaffer

Generalized linear mixed models (GLMM) are commonly used to analyze clustered data, but when the number of clusters is small to moderate, standard statistical tests may produce elevated type I error rates. Small-sample corrections have been…

统计方法学 · 统计学 2023-11-07 Hongxiang Qiu , Andrea J. Cook , Jennifer F. Bobb

To achieve the goal of providing the best possible care to each patient, physicians need to customize treatments for patients with the same diagnosis, especially when treating diseases that can progress further and require additional…

统计方法学 · 统计学 2022-10-25 Xiao Li , Brent R Logan , S M Ferdous Hossain , Erica E M Moodie

Dynamic treatment regimes (DTRs) have received an increasing interest in recent years. DTRs are sequences of treatment decision rules tailored to patient-level information. The main goal of the DTR study is to identify an optimal DTR, a…

统计方法学 · 统计学 2024-04-09 Dan Liu , Wenqing He

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…

统计方法学 · 统计学 2024-10-03 Bingkai Wang , Fan Li , Mengxin Yu

Cluster randomized trials (CRTs) are studies where treatment is randomized at the cluster level but outcomes are typically collected at the individual level. When CRTs are employed in pragmatic settings, baseline population characteristics…

统计方法学 · 统计学 2023-06-22 Mary M. Ryan , Denise Esserman , Fan Li

Sequential multiple assignment randomized trials mimic the actual treatment processes experienced by physicians and patients in clinical settings and inform the comparative effectiveness of dynamic treatment regimes. In such trials,…

统计方法学 · 统计学 2025-04-07 Zi Wang , Yu Cheng , Abdus S. Wahed

Personalized intervention strategies, in particular those that modify treatment based on a participant's own response, are a core component of precision medicine approaches. Sequential Multiple Assignment Randomized Trials (SMARTs) are…

Non-adherence to assigned treatment is a common issue in cluster randomised trials (CRTs). In these settings, the efficacy estimand may be also of interest. Many methodological contributions in recent years have advocated using instrumental…

统计方法学 · 统计学 2018-12-05 Schadrac C. Agbla , Bianca De Stavola , Karla DiazOrdaz