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Improved two-step analysis of germination data from complex experimental designs

Published online by Cambridge University Press:  04 December 2020

Signe M. Jensen
Affiliation:
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegård Allé 13, DK-2630Taastrup, Denmark
Dustin Wolkis
Affiliation:
Department of Science & Conservation, National Tropical Botanical Garden, 3530 Papalina Road, Kalāheo, HI 96741, USA Natural History Museum of Denmark, Faculty of Science, University of Copenhagen, Øster Voldgade 5-7, DK-1350Copenhagen, Denmark
Eshagh Keshtkar
Affiliation:
Department of Agronomy, Faculty of Agriculture, Tarbiat Modares University, PO Box 14115-336, Tehran, Iran
Jens C. Streibig
Affiliation:
Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Højbakkegård Allé 13, DK-2630Taastrup, Denmark
Christian Ritz*
Affiliation:
Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958Frederiksberg C, Denmark
*
Author for correspondence: Signe M. Jensen, E-mail: ritz@nexs.ku.dk

Abstract

Germination experiments are becoming increasingly complex and they are now routinely involving several experimental factors. Recently, a two-step approach utilizing meta-analysis methodology has been proposed for the estimation of hierarchical models suitable for describing data from such complex experiments. Step 1 involves fitting models to data from each sub-experiment, whereas Step 2 involves combination estimates from all model fits obtained in Step 1. However, one shortcoming of this approach was that visualization of resulting fitted germination curves was difficult. Here, we describe in detail an improved two-step analysis that allows visualization of cumulated data together with fitted curves and confidence bands. Also, we demonstrate in detail, through two examples, how to carry out the statistical analysis in practice.

Type
Short Communication
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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