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.
Original language | English |
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Pages (from-to) | 86-102 |
Number of pages | 17 |
Journal | International Journal of Data Mining and Bioinformatics |
Volume | 25 |
Issue number | 1-2 |
DOIs | |
State | Published - 2021 |
Bibliographical note
Publisher Copyright:© 2021 Inderscience Enterprises Ltd.. All rights reserved.
Keywords
- Correlated data
- Crossover design
- Generalised estimating equation model
- Local odds ratio
- Mixed effects model