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

Publikation: Bidrag til tidsskriftLetterForskningfagfællebedømt

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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.

I: Seed Science Research, Bind 27, Nr. 4, 12.2017, s. 321-327.

Publikation: Bidrag til tidsskriftLetterForskningfagfællebedømt

Harvard

Jensen, SM, Andreasen, C, Streibig, JC, Keshtkar, E & Ritz, C 2017, 'A note on the analysis of germination data from complex experimental designs', Seed Science Research, bind 27, nr. 4, s. 321-327. https://doi.org/10.1017/S0960258517000228

APA

Jensen, S. M., Andreasen, C., Streibig, J. C., Keshtkar, E., & Ritz, C. (2017). A note on the analysis of germination data from complex experimental designs. Seed Science Research, 27(4), 321-327. https://doi.org/10.1017/S0960258517000228

Vancouver

Jensen SM, Andreasen C, Streibig JC, Keshtkar E, Ritz C. A note on the analysis of germination data from complex experimental designs. Seed Science Research. 2017 dec;27(4):321-327. https://doi.org/10.1017/S0960258517000228

Author

Jensen, Signe Marie ; Andreasen, Christian ; Streibig, Jens Carl ; Keshtkar, Eshagh ; Ritz, Christian. / A note on the analysis of germination data from complex experimental designs. I: Seed Science Research. 2017 ; Bind 27, Nr. 4. s. 321-327.

Bibtex

@article{3527eed31d34424b9524b734dc597d75,
title = "A note on the analysis of germination data from complex experimental designs",
abstract = "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.",
keywords = "Between-experiment variation, Gerbera hybrida, Log-logistic function, Meta analysis, Mixed model, Randomized complete block design, Time-to-event data",
author = "Jensen, {Signe Marie} and Christian Andreasen and Streibig, {Jens Carl} and Eshagh Keshtkar and Christian Ritz",
note = "CURIS 2017 NEXS 290",
year = "2017",
month = dec,
doi = "10.1017/S0960258517000228",
language = "English",
volume = "27",
pages = "321--327",
journal = "Seed Science Research",
issn = "0960-2585",
publisher = "Cambridge University Press",
number = "4",

}

RIS

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