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

Title
Evaluation of statistical methods for the analysis of crossover designs with repeated measurements
Authors
Kamruzzaman, MdKim, YonggabLim, YeniKwon, OranPark, Taesung
Ewha Authors
권오란임예니
SCOPUS Author ID
권오란scopus; 임예니scopus
Issue Date
2021
Journal Title
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
ISSN
1748-5673JCR Link

1748-5681JCR Link
Citation
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS vol. 25, no. 44198.0, pp. 86 - 102
Keywords
correlated datacrossover designmixed effects modelgeneralised estimating equation modellocal odds ratio
Publisher
INDERSCIENCE ENTERPRISES LTD
Indexed
SCIE; SCOPUS WOS
Document Type
Article
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.
DOI
10.1504/IJDMB.2021.116889
Appears in Collections:
신산업융합대학 > 식품영양학과 > Journal papers
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