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When an experimenter has the option of running an adaptive trial, is it admissible to ignore this option and run a non-adaptive trial instead? We provide a negative answer to this question in the best-arm identification problem, where the…

Machine Learning · Statistics 2025-06-06 Guido Imbens , Chao Qin , Stefan Wager

Clinical trials with a hybrid control arm (a control arm constructed from a combination of randomized patients and real-world data on patients receiving usual care in standard clinical practice) have the potential to decrease the cost of…

Methodology · Statistics 2021-08-20 Joanna Harton , Brian Segal , Ronac Mamtani , Nandita Mitra , Rebecca Hubbard

Adaptive designs have been proposed for clinical trials in which the nuisance parameters or alternative of interest are unknown or likely to be misspecified before the trial. Whereas most previous works on adaptive designs and mid-course…

Methodology · Statistics 2011-05-18 Jay Bartroff , Tze Leung Lai

For randomized clinical trials where a single, primary, binary endpoint would require unfeasibly large sample sizes, composite endpoints are widely chosen as the primary endpoint. Despite being commonly used, composite endpoints entail…

Methodology · Statistics 2022-09-27 Marta Bofill Roig , Guadalupe Gómez Melis , Martin Posch , Franz Koenig

Meta-analyses frequently include trials that report multiple effect sizes based on a common set of study participants. These effect sizes will generally be correlated. Cluster-robust variance-covariance estimators are a fruitful approach…

Methodology · Statistics 2022-03-07 Thilo Welz , Wolfgang Viechtbauer , Markus Pauly

Complete randomization balances covariates on average, but covariate imbalance often exists in finite samples. Rerandomization can ensure covariate balance in the realized experiment by discarding the undesired treatment assignments. Many…

Methodology · Statistics 2022-07-07 Xin Lu , Tianle Liu , Hanzhong Liu , Peng Ding

Randomization is a common technique used in clinical trials to eliminate potential bias and confounders in a patient population. Equal allocation to treatment groups is the standard due to its optimal efficiency in many cases. However, in…

Applications · Statistics 2020-04-09 Thevaa Chandereng , Xiaodan Wei , Rick Chappell

Cluster randomized trials (CRTs) randomly assign an intervention to groups of individuals (e.g., clinics or communities) and measure outcomes on individuals in those groups. While offering many advantages, this experimental design…

Minimizing the number of patients exposed to potentially harmful drugs in early onco logical trials is a major concern during planning. Adaptive designs account for the inherent uncertainty about the true effect size by determining the…

Applications · Statistics 2016-05-03 Kevin Kunzmann , Meinhard Kieser

Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire…

Methodology · Statistics 2023-03-01 Dae Woong Ham , Iavor Bojinov , Michael Lindon , Martin Tingley

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

The traditional model specification of stepped-wedge cluster-randomized trials assumes a homogeneous treatment effect across time while adjusting for fixed-time effects. However, when treatment effects vary over time, the constant effect…

The development of cluster computing frameworks has allowed practitioners to scale out various statistical estimation and machine learning algorithms with minimal programming effort. This is especially true for machine learning problems…

Machine Learning · Statistics 2019-06-24 Robin Vogel , Aurélien Bellet , Stephan Clémençon , Ons Jelassi , Guillaume Papa

We consider learning personalized assignments to one of many treatment arms from a randomized controlled trial. Standard methods that estimate heterogeneous treatment effects separately for each arm may perform poorly in this case due to…

Machine Learning · Statistics 2023-11-02 Rahul Ladhania , Jann Spiess , Lyle Ungar , Wenbo Wu

Background: Stepped wedge cluster randomized trials (SW-CRTs) involve sequential measurements within clusters over time. Initially, all clusters start in the control condition before crossing over to the intervention on a staggered…

Methodology · Statistics 2026-01-21 Jale Basten , Katja Ickstadt , Nina Timmesfeld

Background. Designing trials to reduce treatment duration is important in several therapeutic areas, including TB and antibiotics. We recently proposed a new randomised trial design to overcome some of the limitations of standard two-arm…

Recently, there as been an increasing interest in the use of heavily restricted randomization designs which enforces balance on observed covariates in randomized controlled trials. However, when restrictions are strict, there is a risk that…

Methodology · Statistics 2021-10-15 Mattias Nordin , Mårten Schultzberg

A sequential multiple assignment randomized trial (SMART) facilitates comparison of multiple adaptive treatment strategies (ATSs) simultaneously. Previous studies have established a framework to test the homogeneity of multiple ATSs by a…

Methodology · Statistics 2022-11-04 Liwen Wu , Junyao Wang , Abdus S. Wahed

Multi-Arm, Multi-Stage (MAMS) clinical trial designs allow for multiple therapies to be compared across a spectrum of clinical trial phases. MAMS designs can be categorized into several overarching design groups, including adaptive designs…

Combinatorial linear semi-bandits (CLS) are widely applicable frameworks of sequential decision-making, in which a learner chooses a subset of arms from a given set of arms associated with feature vectors. Existing algorithms work poorly…

Machine Learning · Statistics 2019-09-11 Kei Takemura , Shinji Ito