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Randomized controlled trials (RCTs) are indispensable for establishing the clinical value of medical artificial-intelligence (AI) tools, yet their high cost and long timelines hinder timely validation as new models emerge rapidly. Here, we…

Machine Learning · Computer Science 2025-11-17 Michael Nercessian , Wenxin Zhang , Alexander Schubert , Daphne Yang , Maggie Chung , Ahmed Alaa , Adam Yala

In stepped wedge cluster randomized trials (SW-CRTs), observations collected under the control condition are, on average, from an earlier time than observations collected under the intervention condition. In a cohort design, participants…

Methodology · Statistics 2023-02-23 Jale Basten , Katja Ickstadt , Nina Timmesfeld

Item Response Theory (IRT) is a well known method for assessing responses from humans in education and psychology. In education, IRT is used to infer student abilities and characteristics of test items from student responses. Interactions…

Artificial Intelligence · Computer Science 2023-07-20 Antti Keurulainen , Isak Westerlund , Oskar Keurulainen , Andrew Howes

Randomised controlled trials (RCTs) are regarded as the gold standard for estimating causal treatment effects on health outcomes. However, RCTs are not always feasible, because of time, budget or ethical constraints. Observational data such…

Methodology · Statistics 2024-02-20 Li Su , Roonak Rezvani , Shaun R. Seaman , Colin Starr , Isaac Gravestock

An optimal dynamic treatment regime (DTR) is a sequence of decision rules aimed at providing the best course of treatments individualized to patients. While conventional DTR estimation uses longitudinal data, such data can also be…

Methodology · Statistics 2025-02-06 Larry Dong , Eleanor Pullenayegum , Rodolphe Thiébaut , Olli Saarela

Investigating the causal relationship between exposure and the time-to-event outcome is an important topic in biomedical research. Previous literature has discussed the potential issues of using the hazard ratio as a marginal causal effect…

Methodology · Statistics 2022-05-05 Zihan Lin , Ai Ni , Bo Lu

Longitudinal observational patient data can be used to investigate the causal effects of time-varying treatments on time-to-event outcomes. Several methods have been developed for controlling for the time-dependent confounding that…

Methodology · Statistics 2021-10-08 Ruth H. Keogh , Jon Michael Gran , Shaun R. Seaman , Gwyneth Davies , Stijn Vansteelandt

Restricted mean survival time (RMST) models have gained popularity when analyzing time-to-event outcomes because RMST models offer more straightforward interpretations of treatment effects with fewer assumptions than hazard ratios commonly…

Methodology · Statistics 2023-10-23 Kaiyuan Hua , Xiaofei Wang , Hwanhee Hong

Accurate models of clinical actions and their impacts on disease progression are critical for estimating personalized optimal dynamic treatment regimes (DTRs) in medical/health research, especially in managing chronic conditions.…

Methodology · Statistics 2021-02-19 William Hua , Hongyuan Mei , Sarah Zohar , Magali Giral , Yanxun Xu

Randomized experiments play a major role in data-driven decision making across many different fields and disciplines. In medicine, for example, randomized controlled trials (RCTs) are the backbone of clinical trial methodology for testing…

Applications · Statistics 2016-08-30 Andrew W. Correia

Sequential multiple assignment randomized trials (SMARTs) are used to construct data-driven optimal intervention strategies for subjects based on their intervention and covariate histories in different branches of health and behavioral…

Methodology · Statistics 2022-04-28 Palash Ghosh , Xiaoxi Yan , Bibhas Chakraborty

Randomized controlled trials (RCTs) are the gold standard for evaluating the causal effect of a treatment; however, they often have limited sample sizes and sometimes poor generalizability. On the other hand, non-randomized, observational…

Methodology · Statistics 2021-09-23 Shuxiao Chen , Bo Zhang , Ting Ye

Randomized controlled trials (RCTs) are the gold standard for evaluating causal effects but are often costly and difficult to scale; consequently, they are frequently augmented with auxiliary external controls in many applications. Prior…

Methodology · Statistics 2026-05-28 Jiawei Shan , Yiteng Tu , Guanbo Wang , Chao Ying , Jiwei Zhao

Causal mediation analysis in cluster-randomized trials (CRTs) is complicated by the presence of multiple mediators, intracluster correlation, and within-cluster interference. Existing mediation methods often fall short in accommodating…

Methodology · Statistics 2026-04-14 Jiaqi Tong , Chao Cheng , Fan Li

Cluster or group randomized trials (CRTs) are increasingly used for both behavioral and system-level interventions, where entire clusters are randomly assigned to a study condition or intervention. Apart from the assigned cluster-level…

Methodology · Statistics 2024-11-19 Shubhadeep Chakraborty , Bo Wang , Ram Tiwari , Samiran Ghosh

Randomized experiments are the gold standard for estimating the causal effects of an intervention. In the simplest setting, each experimental unit is randomly assigned to receive treatment or control, and then the outcomes in each treatment…

Methodology · Statistics 2020-06-05 Guillaume Basse , Yi Ding , Panos Toulis

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…

Methodology · Statistics 2023-09-26 Timothy Lycurgus , Amy Kilbourne , Daniel Almirall

Researchers often run resource-intensive randomized controlled trials (RCTs) to estimate the causal effects of interventions on outcomes of interest. Yet these outcomes are often noisy, and estimated overall effects can be small or…

Econometrics · Economics 2023-12-21 Jann Spiess , Vasilis Syrgkanis , Victor Yaneng Wang

Background: Adaptive interventions provide a guide for using ongoing information about individuals to decide whether and how to modify the type, amount, delivery modality, or timing of treatment, to improve intervention effectiveness while…

Methodology · Statistics 2026-03-12 John J. Dziak , Inbal Nahum-Shani

Stepped wedge cluster randomized trials (SWCRTs) often face challenges with potential confounding by time trends. Traditional frequentist methods can fail to provide adequate coverage of the intervention's true effect using confidence…

Methodology · Statistics 2024-02-02 Danni Wu , Hyung G. Park , Corita R. Grudzen , Keith S. Goldfeld
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