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

• Autorzy: Mirosław Krzysko , Tadeusz Smiałowski , Waldemar Wołynski
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

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

• Wydawca: De Gruyter Open
• Czasopismo: Biometrical Letters
• Rocznik: 2014
• Tom: 51
• Numer: 2
• Strony: 103-114

Daty

wydano

2014-12-01

online

2014-12-20

Twórcy

autor

Mirosław Krzysko

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

autor

Tadeusz Smiałowski

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

autor

Waldemar Wołynski

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

Bibliografia

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Identyfikatory

DOI

10.2478/bile-2014-0008