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Optimal two-treatment crossover designs for binary response models

2015/05/11 by Siuli Mukhopadhyay, Mukhopadhyay, S., Satya Prakash Singh +3
Chemistry · Decision Sciences · Mathematics · #FOS: Computer and information sciences #Methodology (stat.ME) #Optimal Experimental Design Methods #Spectroscopy and Chemometric Analyses #Statistical Methods in Clinical Trials

paper · pdf · doi:10.48550/arxiv.1505.02488

openalex publication_date 2015/05/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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 2p possible treatment sequences. An appropriate logistic regression model is postulated and the within subject covariances are modeled through a working correlation matrix. The marginal mean of the binary responses are fitted using generalized estimating equations. The efficiencies of some crossover designs for p=2,3,4 periods are calculated. The effect of misspecified working correlation matrix on design efficiency is also studied.

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