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Related papers: Optimal Crossover Designs for Generalized Linear M…

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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

With the help of Generalized Estimating Equations, we identify locally D-optimal crossover designs for generalized linear models. We adopt the variance of parameters of interest as the objective function, which is minimized using…

Methodology · Statistics 2023-09-11 Jeevan Jankar , Jie Yang , Abhyuday Mandal

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

Cumulative link models have been widely used for ordered categorical responses. Uniform allocation of experimental units is commonly used in practice, but often suffers from a lack of efficiency. We consider D-optimal designs with ordered…

Statistics Theory · Mathematics 2017-11-09 Jie Yang , Liping Tong , Abhyuday Mandal

Crossover designs randomly assign each unit to receive a sequence of treatments. By comparing outcomes within the same unit, these designs can effectively eliminate between-unit variation and facilitate the identification of both…

Methodology · Statistics 2026-04-21 Zhichao Jiang , Peng Ding

Many chemical and biological experiments involve multiple treatment factors and often it is convenient to fit a nonlinear model in these factors. This nonlinear model can be mechanistic, empirical or a hybrid of the two. Motivated by…

Computation · Statistics 2018-10-09 Yuanzhi Huang , Steven Gilmour , Kalliopi Mylona , Peter Goos

The issue of determining not only an adequate dose but also a dosing frequency of a drug arises frequently in Phase II clinical trials. This results in the comparison of models which have some parameters in common. Planning such studies…

Methodology · Statistics 2017-11-16 Kirsten Schorning , Maria Konstantinou

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

Optimal designs for generalized linear models require a prior knowledge of the regression parameters. At certain values of the parameters we propose particular assumptions which allow to derive a locally optimal design for a model without…

Statistics Theory · Mathematics 2019-06-26 Osama Idais

This article discusses $A$-, $D$- and $E$-optimality results for multivariate crossover designs, where more than one response is measured from every period for each subject. The motivation for these multivariate designs comes from a $3…

Methodology · Statistics 2025-09-22 Shubham Niphadkar , Siuli Mukhopadhyay

We give an overview over the usefulness of the concept of equivariance and invariance in the design of experiments for generalized linear models. In contrast to linear models here pairs of transformations have to be considered which act…

Statistics Theory · Mathematics 2020-11-20 Osama Idais , Rainer Schwabe

We consider the optimal experimental design problem of allocating subjects to treatment or control when subjects participate in multiple, separate controlled experiments within a short time-frame and subject covariate information is…

Methodology · Statistics 2024-12-16 William Fisher , Qiong Zhang , Lulu Kang , Xinwei Deng

This paper deals exclusively with crossover designs for the purpose of comparing t test treatments with a control treatment when the number of periods is no larger than t+1. Among other results it specifies sufficient conditions for a…

Statistics Theory · Mathematics 2007-06-13 A. S. Hedayat , Min Yang

A model for cross-over designs with repeated measures within each period was developed. It is obtained using an extension of generalized estimating equations that includes a parametric component to model treatment effects and a…

Methodology · Statistics 2023-03-21 N. A. Cruz , O. O. Melo , C. A. Martinez

Generalized linear models (GLMs) have been used widely for modelling the mean response both for discrete and continuous random variables with an emphasis on categorical response. Recently Yang, Mandal and Majumdar (2013) considered full…

Statistics Theory · Mathematics 2013-05-06 Jie Yang , Abhyuday Mandal

The gamma model is a generalized linear model for gamma-distributed outcomes. The model is widely applied in psychology, ecology or medicine. In this paper we focus on gamma models having a linear predictor without intercept. For a specific…

Statistics Theory · Mathematics 2019-04-22 Osama Idais , Rainer Schwabe

We consider repeated measurement designs when a residual or carry-over effect may be present in at most one later period. Since assuming an additive model may be unrealistic for some applications and leads to biased estimation of treatment…

Statistics Theory · Mathematics 2014-11-20 R. A. Bailey , P. Druilhet

We consider an experiment with two qualitative factors at 2 levels each and a binary response, that follows a generalized linear model. In Mandal, Yang and Majumdar (2010) we obtained basic results and characterizations of locally D-optimal…

Methodology · Statistics 2015-03-17 Jie Yang , Abhyuday Mandal , Dibyen Majumdar

In this article, universally optimal multivariate crossover designs are studied. The multiple response crossover design is motivated by a $3 \times 3$ crossover setup, where the effect of $3$ doses of an oral drug are studied on gene…

Methodology · Statistics 2024-07-16 Shubham Niphadkar , Siuli Mukhopadhyay

We consider optimal designs for general multinomial logistic models, which cover baseline-category, cumulative, adjacent-categories, and continuation-ratio logit models, with proportional odds, non-proportional odds, or partial proportional…

Statistics Theory · Mathematics 2019-02-19 Xianwei Bu , Dibyen Majumdar , Jie Yang
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