A note on the analysis of germination data from complex experimental designs

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In recent years germination experiments have become more and more complex. Typically, they are replicated in time as independent runs and at each time point they involve hierarchical, often factorial experimental designs, which are now commonly analysed by means of linear mixed models. However, in order to characterize germination in response to time elapsed, specific event-time models are needed and mixed model extensions of these models are not readily available, neither in theory nor in practice. As a practical workaround we propose a two-step approach that combines and weighs together results from event-time models fitted separately to data from each germination test by means of meta-analytic random effects models. We show that this approach provides a more appropriate appreciation of the sources of variation in hierarchically structured germination experiments as both between- and within-experiment variation may be recovered from the data.

Original languageEnglish
JournalSeed Science Research
Volume27
Issue number4
Pages (from-to)321-327
Number of pages7
ISSN0960-2585
DOIs
Publication statusPublished - Dec 2017

    Research areas

  • Between-experiment variation, Gerbera hybrida, Log-logistic function, Meta analysis, Mixed model, Randomized complete block design, Time-to-event data

ID: 185180122