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

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 - 2017/12/1

Y1 - 2017/12/1

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

SN - 0960-2585

VL - 27

SP - 321

EP - 327

JO - Seed Science Research

JF - Seed Science Research

IS - 4

ER -