<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Umultowska 87, 61-614 Poznan, Poland

Plant Breeding and Acclimatization Institute, National Research Institute, Radzików, 05-870 Błonie, Poland

Biometrical Letters

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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...

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Online veröffentlicht: 20. Dez. 2014

Seitenbereich: 103 - 114

DOI: https://doi.org/10.2478/bile-2014-0008

Schlüsselwörter
multivariate repeated measures data (doubly multivariate data), Kronecker product covariance structure, maximum likelihood estimates, mixed MANOVA model, principal component analysis

© by Mirosław Krzysko

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Analysis of multivariate repeated measures data using a MANOVA model and principal components

Online veröffentlicht: 20. Dez. 2014

Seitenbereich: 103 - 114

DOI: https://doi.org/10.2478/bile-2014-0008

Schlüsselwörtermultivariate repeated measures data (doubly multivariate data), Kronecker product covariance structure, maximum likelihood estimates, mixed MANOVA model, principal component analysis

© by Mirosław Krzysko

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
multivariate repeated measures data (doubly multivariate data), Kronecker product covariance structure, maximum likelihood estimates, mixed MANOVA model, principal component analysis