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Hierarchical random effect models are used for different purposes in clinical research and other areas. In general, the main focus is on population parameters related to the expected treatment effects or group differences among all units of…

Applications · Statistics 2021-04-07 Maryna Prus , Norbert Benda , Rainer Schwabe

We propose a flexible design for the identification of optimal dose combinations in dual-agent dose-finding clinical trials. The design is called AAA, standing for three adaptations: adaptive model selection, adaptive dose insertion, and…

Methodology · Statistics 2017-06-13 Jiaying Lyu , Yuan Ji , Naiqing Zhao , Daniel V. T. Catenacci

We propose novel optimal designs for longitudinal data for the common situation where the resources for longitudinal data collection are limited, by determining the optimal locations in time where measurements should be taken. As for all…

Methodology · Statistics 2016-04-20 Hao Ji , Hans-Georg Müller

The treatment assignment mechanism in a randomized clinical trial can be optimized for statistical efficiency within a specified class of randomization mechanisms. Optimal designs of this type have been characterized in terms of the…

Methodology · Statistics 2025-09-03 Wei Zhang , Zhiwei Zhang , Aiyi Liu

The subject of this work is multiple group random coefficients regression models with several treatments and one control group. Such models are often used for studies with cluster randomized trials. We investigate A-, D- and E-optimal…

Statistics Theory · Mathematics 2018-07-27 Maryna Prus

We construct optimal designs for group testing experiments where the goal is to estimate the prevalence of a trait by using a test with uncertain sensitivity and specificity. Using optimal design theory for approximate designs, we show that…

Statistics Theory · Mathematics 2017-01-05 Shih-Hao Huang , Mong-Na Lo Huang , Kerby Shedden , Weng Kee Wong

There are multiple cluster randomised trial designs that vary in when the clusters cross between control and intervention states, when observations are made within clusters, and how many observations are made at that time point. Identifying…

Methodology · Statistics 2023-07-20 Samuel I. Watson , Alan Girling , Karla Hemming

Randomized saturation designs are a family of designs which assign a possibly different treatment proportion to each cluster of a population at random. As a result, they generalize the well-known (stratified) completely randomized designs…

Methodology · Statistics 2022-03-21 Chencheng Cai , Jean Pouget-Abadie , Edoardo M. Airoldi

Sequential experimental design to discover interventions that achieve a desired outcome is a key problem in various domains including science, engineering and public policy. When the space of possible interventions is large, making an…

Machine Learning · Computer Science 2023-08-17 Jiaqi Zhang , Louis Cammarata , Chandler Squires , Themistoklis P. Sapsis , Caroline Uhler

Optimum experimental design theory has recently been extended for parameter estimation in copula models. However, the choice of the correct dependence structure still requires wider analyses. In this work the issue of copula selection is…

Methodology · Statistics 2016-01-29 Elisa Perrone , Andreas Rappold , Werner G. Müller

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

Phase 1-2 designs provide a methodological advance over phase 1 designs for dose finding by using both clinical response and toxicity. A phase 1-2 trial still may fail to select a truly optimal dose. because early response is not a perfect…

Applications · Statistics 2024-04-03 Cheng-Han Yang , Peter F. Thall , Ruitao Lin

Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design require knowledge of operating characteristics of competing…

Computation · Statistics 2025-03-11 Michael Sweeting , Daniel Slade , Dan Jackson , Kristian Brock

Optimal block designs in small blocks are explored when the treatments have a natural ordering and interest lies in comparing consecutive pairs of treatments. We first develop an approximate theory which leads to a convenient multiplicative…

Statistics Theory · Mathematics 2014-05-20 S. Huda , Rahul Mukerjee

An important tool to evaluate the performance of any design is an optimal benchmark proposed by O'Quigley and others (2002, Biostatistics 3(1), 51-56) that provides an upper bound on the performance of a design under a given scenario. The…

Statistics Theory · Mathematics 2018-03-06 Pavel Mozgunov , Thomas Jaki , Xavier Paoletti

Interval designs are a class of phase I trial designs for which the decision of dose assignment is determined by comparing the observed toxicity rate at the current dose with a prespecified (toxicity tolerance) interval. If the observed…

Methodology · Statistics 2013-09-20 Suyu Liu , Ying Yuan

In this article, an adaption of an algorithm for the creation of experimental designs by Lekivetz and Jones (2015) is suggested, dealing with constraints around randomization. Split-plot design of experiments is used, when the levels of…

Methodology · Statistics 2020-03-24 Thomas Muehlenstaedt , Maria Lanzerath

The purpose of a phase I dose-finding clinical trial is to investigate the toxicity profiles of various doses for a new drug and identify the maximum tolerated dose. Over the past three decades, various dose-finding designs have been…

Methodology · Statistics 2021-11-25 Yunshan Duan , Shijie Yuan , Yuan Ji , Peter Mueller

We review recent literature that proposes to adapt ideas from classical model based optimal design of experiments to problems of data selection of large datasets. Special attention is given to bias reduction and to protection against…

Methodology · Statistics 2018-12-03 Elena Pesce , Eva Riccomagno

We study the problem of a decision maker who must provide the best possible treatment recommendation based on an experiment. The desirability of the outcome distribution resulting from the policy recommendation is measured through a…

Econometrics · Economics 2022-04-06 Anders Bredahl Kock , David Preinerstorfer , Bezirgen Veliyev