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This paper develops a nonparametric model that represents how sequences of outcomes and treatment choices influence one another in a dynamic manner. In this setting, we are interested in identifying the average outcome for individuals in…

Econometrics · Economics 2019-01-16 Sukjin Han

Random allocation models used in clinical trials aid researchers in determining which of a particular treatment provides the best results by reducing bias between groups. Often however, this determination leaves researchers battling ethical…

Applications · Statistics 2020-08-04 Albert. H. Lee , Edward L Boone , Roy T. Sabo , Erin Donahue

In clinical trials, there is potential to improve precision and reduce the required sample size by appropriately adjusting for baseline variables in the statistical analysis. This is called covariate adjustment. Despite recommendations by…

Methodology · Statistics 2022-06-20 Kelly Van Lancker , Joshua Betz , Michael Rosenblum

Various adaptive randomization procedures (adaptive designs) have been proposed to clinical trials. This paper discusses several broad families of procedures, such as the play-the-winner rule and Markov chain model, randomized…

Statistics Theory · Mathematics 2009-08-30 Li-Xin Zhang

Dose-finding studies are frequently conducted to evaluate the effect of different doses or concentration levels of a compound on a response of interest. Applications include the investigation of a new medicinal drug, a herbicide or…

Applications · Statistics 2011-08-01 Björn Bornkamp , Frank Bretz , Holger Dette , José Pinheiro

Optimal treatment rules can improve health outcomes on average by assigning a treatment associated with the most desirable outcome to each individual. Due to an unknown data generation mechanism, it is appealing to use flexible models to…

Methodology · Statistics 2023-11-21 Lingjie Shen , Gijs Geleijnse , Maurits Kaptein

There has been significant attention given to developing data-driven methods for tailoring patient care based on individual patient characteristics. Dynamic treatment regimes formalize this through a sequence of decision rules that map…

Methodology · Statistics 2022-02-22 Eric J. Rose , Erica E. M. Moodie , Susan Shortreed

An innovative sampling strategy is proposed, which applies to large-scale population-based surveys targeting a rare trait that is unevenly spread over a geographical area of interest. Our proposal is characterised by the ability to tailor…

Methodology · Statistics 2020-04-07 Fulvia Mecatti , Charalambos Sismanidis , Emanuela Furfaro

Adaptive approaches, allowing for more flexible trial design, have been proposed for individually randomized trials to save time or reduce sample size. However, adaptive designs for cluster-randomized trials in which groups of participants…

Methodology · Statistics 2022-01-10 Junwei Shen , Shirin Golchi , Erica E. M. Moodie , David Benrimoh

Balancing influential covariates is crucial for valid treatment comparisons in clinical studies. While covariate-adaptive randomization is commonly used to achieve balance, its performance can be inadequate when the number of baseline…

Methodology · Statistics 2024-12-30 Ziqing Guo , Yang Liu , Lucy Xia

Sequential allocation is a simple and widely studied mechanism to allocate indivisible items in turns to agents according to a pre-specified picking sequence of agents. At each turn, the current agent in the picking sequence picks its most…

Data Structures and Algorithms · Computer Science 2019-09-17 Mingyu Xiao , Jiaxing Ling

Adaptive seamless designs combine confirmatory testing, a domain of phase III trials, with features such as treatment or subgroup selection, typically associated with phase II trials. They promise to increase the efficiency of development…

Methodology · Statistics 2019-01-25 Tim Friede , Nigel Stallard , Nicholas Parsons

Applications of artificial intelligence (AI) in drug development continue to increase at a rapid pace. Regulatory authorities have provided increasingly clear perspectives on the use of AI in regulated applications, including recent draft…

Applications · Statistics 2026-05-25 Aaron M. Smith , Tala Fakhouri , Run Zhuang , Jonathan R. Walsh

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

We consider the following comparative effectiveness scenario. There are two treatments for a particular medical condition: a randomized experiment has demonstrated mediocre effectiveness for the first treatment, while a non-randomized study…

Methodology · Statistics 2024-08-23 Brian Knaeble , Erich Kummerfeld

The offline time of the reduced basis method can be very long given a large training set of parameter samples. This usually happens when the system has more than two independent parameters. On the other hand, if the training set includes…

Numerical Analysis · Mathematics 2023-04-04 Sridhar Chellappa , Lihong Feng , Peter Benner

Indirect experiments provide a valuable framework for estimating treatment effects in situations where conducting randomized control trials (RCTs) is impractical or unethical. Unlike RCTs, indirect experiments estimate treatment effects by…

Machine Learning · Computer Science 2023-12-06 Yash Chandak , Shiv Shankar , Vasilis Syrgkanis , Emma Brunskill

We consider a decision maker who must choose an action in order to maximize a reward function that depends also on an unknown parameter {\Theta}. The decision maker can delay taking the action in order to experiment and gather additional…

Machine Learning · Statistics 2021-06-22 Victor F. Araman , Rene Caldentey

Response-adaptive randomization (RAR) has been studied extensively in conventional, single-stage clinical trials, where it has been shown to yield ethical and statistical benefits, especially in trials with many treatment arms. However, RAR…

Methodology · Statistics 2024-01-09 Peter Norwood , Marie Davidian , Eric Laber

Significant evidence has become available that emphasizes the importance of personalization in medicine. In fact, it has become a common belief that personalized medicine is the future of medicine. The core of personalized medicine is the…

Methodology · Statistics 2020-04-30 Qiong Zhang , Amin Khademi , Yongjia Song
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