A note on the analysis of germination data from complex experimental designs
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A note on the analysis of germination data from complex experimental designs. / Jensen, Signe Marie; Andreasen, Christian; Streibig, Jens Carl; Keshtkar, Eshagh; Ritz, Christian.
In: Seed Science Research, Vol. 27, No. 4, 12.2017, p. 321-327.Research output: Contribution to journal › Letter › Research › peer-review
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TY - JOUR
T1 - A note on the analysis of germination data from complex experimental designs
AU - Jensen, Signe Marie
AU - Andreasen, Christian
AU - Streibig, Jens Carl
AU - Keshtkar, Eshagh
AU - Ritz, Christian
N1 - CURIS 2017 NEXS 290
PY - 2017/12
Y1 - 2017/12
N2 - 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.
AB - 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.
KW - Between-experiment variation
KW - Gerbera hybrida
KW - Log-logistic function
KW - Meta analysis
KW - Mixed model
KW - Randomized complete block design
KW - Time-to-event data
U2 - 10.1017/S0960258517000228
DO - 10.1017/S0960258517000228
M3 - Letter
AN - SCOPUS:85030841953
VL - 27
SP - 321
EP - 327
JO - Seed Science Research
JF - Seed Science Research
SN - 0960-2585
IS - 4
ER -
ID: 185180122