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Randomized experiments have been the gold standard for assessing the effectiveness of a treatment or policy. The classical complete randomization approach assigns treatments based on a prespecified probability and may lead to inefficient…

Methodology · Statistics 2023-10-26 Waverly Wei , Xinwei Ma , Jingshen Wang

An individualized dose rule recommends a dose level within a continuous safe dose range based on patient level information such as physical conditions, genetic factors and medication histories. Traditionally, personalized dose finding…

Methodology · Statistics 2020-07-21 Liangyu Zhu , Wenbin Lu , Michael R. Kosorok , Rui Song

Personalized decision-making, aiming to derive optimal treatment regimes based on individual characteristics, has recently attracted increasing attention in many fields, such as medicine, social services, and economics. Current literature…

Methodology · Statistics 2023-02-28 Jianing Chu , Wenbin Lu , Shu Yang

We consider a multi-armed bandit problem with covariates. Given a realization of the covariate vector, instead of targeting the treatment with highest conditional expectation, the decision maker targets the treatment which maximizes a…

Machine Learning · Statistics 2024-12-25 Anders Bredahl Kock , David Preinerstorfer , Bezirgen Veliyev

The increasing prevalence of rich sources of data and the availability of electronic medical record databases and electronic registries opens tremendous opportunities for enhancing medical research. For example, controlled trials are…

Methodology · Statistics 2015-09-23 Liwen Ouyang , Daniel W. Apley , Sanjay Mehrotra

The field of precision medicine aims to tailor treatment based on patient-specific factors in a reproducible way. To this end, estimating an optimal individualized treatment regime (ITR) that recommends treatment decisions based on patient…

In sequential experiments, subjects become available for the study over a period of time, and covariates are often measured at the time of arrival. We consider the setting where the sample size is fixed but covariate values are unknown…

Methodology · Statistics 2020-05-28 Mia S. Tackney , David C. Woods , Ilya Shpitser

A treatment regime is a deterministic function that dictates personalized treatment based on patients' individual prognostic information. There is a fast-growing interest in finding optimal treatment regimes to maximize expected long-term…

Statistics Theory · Mathematics 2016-11-25 Runchao Jiang , Wenbin Lu , Rui Song , Marie Davidian

We consider the problem of evaluating designs for a two-arm randomized experiment with the criterion being the power of the randomization test for the one-sided null hypothesis. Our evaluation assumes a response that is linear in one…

Methodology · Statistics 2020-08-14 Abba M. Krieger , David Azriel , Michael Sklar , Adam Kapelner

Targeted therapies on the basis of genomic aberrations analysis of the tumor have shown promising results in cancer prognosis and treatment. Regardless of tumor type, trials that match patients to targeted therapies for their particular…

Applications · Statistics 2018-04-18 Yanxun Xu , Peter Mueller , Apostolia M Tsimberidou , Donald Berry

A treatment regime formalizes personalized medicine as a function from individual patient characteristics to a recommended treatment. A high-quality treatment regime can improve patient outcomes while reducing cost, resource consumption,…

Methodology · Statistics 2015-04-30 Yichi Zhang , Eric B. Laber , Anastasios Tsiatis , Marie Davidian

Controlled experiments are widely used in many applications to investigate the causal relationship between input factors and experimental outcomes. A completely randomized design is usually used to randomly assign treatment levels to…

Methodology · Statistics 2026-05-12 Yiou Li , Lulu Kang , Xiao Huang

Background: trials to identify the minimal effective treatment duration are needed in different therapeutic areas, including bacterial infections, TB and Hepatitis--C. However, standard non-inferiority designs have several limitations,…

Dynamic treatment regimes are treatment allocations tailored to heterogeneous individuals. The optimal dynamic treatment regime is a regime that maximizes counterfactual welfare. We introduce a framework in which we can partially learn the…

Econometrics · Economics 2021-07-14 Sukjin Han

Optimal treatment regimes are personalized policies for making a treatment decision based on subject characteristics, with the policy chosen to maximize some value. It is common to aim to maximize the mean outcome in the population, via a…

Methodology · Statistics 2022-02-28 Liu Leqi , Edward H. Kennedy

We present a probabilistic ranking model to identify the optimal treatment in multiple-response experiments. In contemporary practice, treatments are applied over individuals with the goal of achieving multiple ideal properties on them…

To promote precision medicine, individualized treatment regimes (ITRs) are crucial for optimizing the expected clinical outcome based on patient-specific characteristics. However, existing ITR research has primarily focused on scenarios…

Methodology · Statistics 2024-02-20 Chang Wang , Lu Wang

Personalized medicine has gained much popularity recently as a way of providing better healthcare by tailoring treatments to suit individuals. Our research, motivated by the UK INTERVAL blood donation trial, focuses on estimating the…

Methodology · Statistics 2023-02-24 Yuejia Xu , Angela M. Wood , David J. Roberts , Brian D. M. Tom

Medical research has evolved conventions for choosing sample size in randomized clinical trials that rest on the theory of hypothesis testing. Bayesians have argued that trials should be designed to maximize subjective expected utility in…

Methodology · Statistics 2018-12-11 Charles F. Manski , Aleksey Tetenov

Breakthroughs in cancer biology have defined new research programs emphasizing the development of therapies that target specific pathways in tumor cells. Innovations in clinical trial design have followed with master protocols defined by…

Methodology · Statistics 2020-07-09 Alexander M. Kaizer , Joseph S. Koopmeiners , Nan Chen , Brian P. Hobbs