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In this paper we consider the problem of constructing $T$-optimal discriminating designs for Fourier regression models. We provide explicit solutions of the optimal design problem for discriminating between two Fourier regression models,…

Methodology · Statistics 2015-12-24 Holger Dette , Viatcheslav B. Melas , Petr Shpilev

This paper considers the problem of constructing optimal discriminating experimental designs for competing regression models on the basis of the T-optimality criterion introduced by Atkinson and Fedorov [Biometrika 62 (1975) 57-70].…

Statistics Theory · Mathematics 2014-01-30 Holger Dette , Viatcheslav B. Melas , Petr Shpilev

Recent advances in diffusion models have demonstrated their strong capabilities in generating high-fidelity samples from complex distributions through an iterative refinement process. Despite the empirical success of diffusion models in…

Robotics · Computer Science 2024-07-03 Chaoyi Pan , Zeji Yi , Guanya Shi , Guannan Qu

Optimal two-treatment, $p$ period crossover designs for binary responses are determined. The optimal designs are obtained by minimizing the variance of the treatment contrast estimator over all possible allocations of $n$ subjects to $2^p$…

Methodology · Statistics 2015-05-12 S. Mukhopadhyay , S. P. Singh , A. Dey

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

Mixed-effect models are very popular for analyzing data with a hierarchical structure, e.g. repeated observations within subjects in a longitudinal design, patients nested within centers in a multicenter design. However, recently, due to…

Methodology · Statistics 2019-05-09 Abhik Ghosh , Magne Thoresen

This work presents a robust design optimization approach for a char combustion process in a limited-data setting, where simulations of the fluid-solid coupled system are computationally expensive. We integrate a polynomial dimensional…

Optimization and Control · Mathematics 2025-03-11 Yulin Guo , Dongjin Lee , Boris Kramer

In recent years, the field of precision medicine has seen many advancements. Significant focus has been placed on creating algorithms to estimate individualized treatment rules (ITR), which map from patient covariates to the space of…

Methodology · Statistics 2021-12-09 Kushal S. Shah , Haoda Fu , Michael R. Kosorok

Randomized experiments can provide unbiased estimates of sample average treatment effects. However, estimates of population treatment effects can be biased when the experimental sample and the target population differ. In this case, the…

Methodology · Statistics 2022-11-10 Wenqi Shi , Xi Lin

Explanations of the internal validity of regression discontinuity designs (RDD) generally appeal to the idea that RDDs are ``as good as" random near the treatment cut point. Cattaneo, Frandsen, and Titiunik (2015) are the first to take this…

Methodology · Statistics 2022-09-26 Sophie Litschwartz

This article discusses D-optimal Bayesian crossover designs for generalized linear models. Crossover trials with t treatments and p periods, for $t <= p$, are considered. The designs proposed in this paper minimize the log determinant of…

Computation · Statistics 2018-08-16 Satya Prakash Singh , Siuli Mukhopadhyay

While a difference-in-differences (DID) design was originally developed with one pre- and one post-treatment period, data from additional pre-treatment periods are often available. How can researchers improve the DID design with such…

Applications · Statistics 2022-02-14 Naoki Egami , Soichiro Yamauchi

A common problem in Phase II clinical trials is the comparison of dose response curves corresponding to different treatment groups. If the effect of the dose level is described by parametric regression models and the treatments differ in…

Statistics Theory · Mathematics 2016-03-16 Chrystel Feller , Kirsten Schorning , Holger Dette , Georgina Bermann , Björn Bornkamp

Model-assisted designs have garnered significant attention in recent years due to their high accuracy in identifying the maximum tolerated dose (MTD) and their operational simplicity. To identify the MTD, they employ estimated dose limiting…

Applications · Statistics 2025-08-19 Rentaro Wakayama , Tomotaka Momozaki , Shuji Ando

We consider convex optimization problems formulated using dynamic programming equations. Such problems can be solved using the Dual Dynamic Programming algorithm combined with the Level 1 cut selection strategy or the Territory algorithm to…

Optimization and Control · Mathematics 2017-05-26 Vincent Guigues

Determining the causal structure of a set of variables is critical for both scientific inquiry and decision-making. However, this is often challenging in practice due to limited interventional data. Given that randomized experiments are…

Methodology · Statistics 2019-02-28 Raj Agrawal , Chandler Squires , Karren Yang , Karthik Shanmugam , Caroline Uhler

Immunotherapies and targeted therapies have gained popularity due to their promising therapeutic effects across multiple treatment areas. The focus of early phase dose-finding clinical trials has shifted from finding the maximum tolerated…

Methodology · Statistics 2023-12-27 Hao Sun , Jieqi Tu

The primary goal of dose allocation in phase I trials is to minimize patient exposure to subtherapeutic or excessively toxic doses, while accurately recommending a phase II dose that is as close as possible to the maximum tolerated dose…

Methodology · Statistics 2025-03-21 Jiapeng Xu , Dehua Bi , Shenghua Kelly Fan , Bee Leng Lee , Ying Lu

Body Dysmorphic Disorder (BDD) is a highly prevalent and frequently underdiagnosed condition characterized by persistent, intrusive preoccupations with perceived defects in physical appearance. In this extended analysis, we employ multiple…

Machine Learning · Computer Science 2025-03-17 Omar Costilla-Reyes , Morgan Talbot

Regression discontinuity (RD) analysis with latent variables as introduced by Morell et al. (2025), offers a useful augmentation of the conventional RD by incorporating measurement model. This approach is particularly relevant in education…

Methodology · Statistics 2026-04-07 Monica Morell , Youngjin Han , Muwon Kwon , Youjin Sung , Yang Liu , Ji Seung Yang
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