Title: Evaluation of statistical methods for the analysis of crossover designs with repeated measurements

Authors: Md. Kamruzzaman; Yonggab Kim; Yeni Lim; Oran Kwon; Taesung Park

Addresses: Department of Statistics, Seoul National University, Gwanak-gu, Seoul, South Korea ' Department of Statistics, Seoul National University, Gwanak-gu, Seoul, South Korea ' Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, South Korea ' Department of Nutritional Science and Food Management, Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, South Korea ' Department of Statistics, Seoul National University, Gwanak-gu, Seoul, South Korea

Abstract: The crossover design is a type of longitudinal study used in clinical trials to evaluate the effectiveness of new drugs and new treatments. In the crossover design, each subject is subsequently switched through all treatments after a washout period. Although the linear mixed-effects model is one of the commonly used methods for crossover designs, sometimes it suffers from convergence problems. In this study, we adopted generalised estimating equations for crossover design by shifting the position of the variables so that the independent variables of the linear mixed models are regarded as the response variables. The advantage of the generalised estimating equation model lies in its simple computation and is relatively easy to use. A simulation study showed that the power of generalised estimating equation models is comparable to or slightly better than that of linear mixed-effects model.

Keywords: correlated data; crossover design; mixed effects model; generalised estimating equation model; local odds ratio.

DOI: 10.1504/IJDMB.2021.116889

International Journal of Data Mining and Bioinformatics, 2021 Vol.25 No.1/2, pp.86 - 102

Received: 09 Mar 2021
Accepted: 05 Apr 2021
Published online: 05 Aug 2021 *

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