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A Mixed Modelling Approach for Randomized Experiments with Repeated Measures

Hans‐Peter PiephoAuthors’ addresses: Prof. Dr H. P. Piepho (corresponding author; e-mail: [email protected]) and Dr A. Büchse, Institut für Pflanzenbau und Grünland, Universität Hohenheim, 70599 Stuttgart, Germany; Doz. Dr C. Richter, Institut für Pflanzenbauwissenschaften, Humboldt-Universität zu Berlin, Berlin, GermanyAndreas BüchseAuthors’ addresses: Prof. Dr H. P. Piepho (corresponding author; e-mail: [email protected]) and Dr A. Büchse, Institut für Pflanzenbau und Grünland, Universität Hohenheim, 70599 Stuttgart, Germany; Doz. Dr C. Richter, Institut für Pflanzenbauwissenschaften, Humboldt-Universität zu Berlin, Berlin, GermanyChristel RichterAuthors’ addresses: Prof. Dr H. P. Piepho (corresponding author; e-mail: [email protected]) and Dr A. Büchse, Institut für Pflanzenbau und Grünland, Universität Hohenheim, 70599 Stuttgart, Germany; Doz. Dr C. Richter, Institut für Pflanzenbauwissenschaften, Humboldt-Universität zu Berlin, Berlin, Germany

2004en

ABI

Annotatsiya

Abstract Repeated measurements on the same experimental unit are common in plant research. Due to lack of randomization and the serial ordering of observations on the same unit, such data give rise to correlations, which need to be accounted for in statistical analysis. Mixed modelling provides a flexible framework for this task. The present paper proposes a general method to formulate mixed models for designed experiments with repeated measurements. The approach is exemplified by way of several examples.

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DOI: 10.1111/j.1439-037x.2004.00097.x

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