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Volume 51 Number 2 pp. 103-114
Mirosław Krzysko 1, Tadeusz Smiałowski 2, Waldemar Wołynski 1
1Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Umultowska 87, 61-614Poznan, Poland
2Plant Breeding and Acclimatization Institute, National Research Institute, Radzików, 05-870Błonie, Poland
2Plant Breeding and Acclimatization Institute, National Research Institute, Radzików, 05-870Błonie, Poland
Analysis of multivariate repeated measures data using a MANOVA model and principal components
Abstract
In this paper we consider a set of T repeated measurements on p characteristics on each of n individuals. The n individuals themselves may be divided and randomly assigned to K groups. These data are analyzed using a mixed effect MANOVA model, assuming that the data on an individual have a covariance matrix which is a Kronecker product of two positive definite matrices. Results are illustrated on a data set obtained from experiments with varieties of winter rye.
Keywords: multivariate repeated measures data (doubly multivariate data), Kronecker product covariance structure, maximum likelihood estimates, mixed MANOVA model, principal component analysis
DOI: 10.2478/bile-2014-0008
For citation:
| MLA | Krzysko, Mirosław, et al. "Analysis of multivariate repeated measures data using a MANOVA model and principal components." Biometrical Letters 51.2 (2014): 103-114. DOI: 10.2478/bile-2014-0008 |
| APA | Krzysko, M., Smiałowski, T., & Wołynski, W. (2014). Analysis of multivariate repeated measures data using a MANOVA model and principal components. Biometrical Letters 51(2), 103-114 DOI: 10.2478/bile-2014-0008 |
| ISO 690 | KRZYSKO, Mirosław, SMIAłOWSKI, Tadeusz, WOłYNSKI, Waldemar. Analysis of multivariate repeated measures data using a MANOVA model and principal components. Biometrical Letters, 2014, 51.2: 103-114. DOI: 10.2478/bile-2014-0008 |