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    Rights statement: This is the peer reviewed version of the following article: Pallmann, P. and Schaarschmidt, F. (2015), Common pitfalls when testing additivity of treatment mixtures with chi-square analyses. Journal of Applied Entomology. 140: 135–141. doi: 10.1111/jen.12258 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jen.12258/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Common pitfalls when testing additivity of treatment mixtures with chi-square analyses

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Common pitfalls when testing additivity of treatment mixtures with chi-square analyses. / Pallmann, Philip; Schaarschmidt, Frank.
In: Journal of Applied Entomology, Vol. 140, No. 1-2, 02.2016, p. 135-141.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Pallmann, P & Schaarschmidt, F 2016, 'Common pitfalls when testing additivity of treatment mixtures with chi-square analyses', Journal of Applied Entomology, vol. 140, no. 1-2, pp. 135-141. https://doi.org/10.1111/jen.12258

APA

Vancouver

Pallmann P, Schaarschmidt F. Common pitfalls when testing additivity of treatment mixtures with chi-square analyses. Journal of Applied Entomology. 2016 Feb;140(1-2):135-141. Epub 2015 Aug 14. doi: 10.1111/jen.12258

Author

Pallmann, Philip ; Schaarschmidt, Frank. / Common pitfalls when testing additivity of treatment mixtures with chi-square analyses. In: Journal of Applied Entomology. 2016 ; Vol. 140, No. 1-2. pp. 135-141.

Bibtex

@article{c18b11a9c87146c4b5d671cc1e1ff99f,
title = "Common pitfalls when testing additivity of treatment mixtures with chi-square analyses",
abstract = "Studying interactions of multiple pesticides applied simultaneously in a mixture is a common task in phytopathology. Statistical methods are employed to test whether the treatment components influence each other's efficacy in a promotive or inhibitory way (synergistic or antagonistic interaction) or rather act independent of one another (additivity). The trouble is that widely used procedures based on chi-square tests are often seriously flawed, either because people apply them in a preposterous way or because the method simply does not fit the problem at hand. Browsing recent volumes of entomological journals, we found that numerous researchers have (in all likelihood unwittingly) analysed their data as if they had had a sample size of 100 or, equally bad, a sample size of one! We show how to avoid such poor practices and further argue that chi-square testing is, even if applied correctly (meaning that no technical errors are made), a limited purpose tool for assessing treatment interactions.",
keywords = "antagonism, integrated pest management, interaction, statistical analysis, synergism",
author = "Philip Pallmann and Frank Schaarschmidt",
note = "This is the peer reviewed version of the following article: Pallmann, P. and Schaarschmidt, F. (2015), Common pitfalls when testing additivity of treatment mixtures with chi-square analyses. Journal of Applied Entomology. 140: 135–141. doi: 10.1111/jen.12258 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jen.12258/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2016",
month = feb,
doi = "10.1111/jen.12258",
language = "English",
volume = "140",
pages = "135--141",
journal = "Journal of Applied Entomology",
issn = "0931-2048",
publisher = "Blackwell Publishing Ltd",
number = "1-2",

}

RIS

TY - JOUR

T1 - Common pitfalls when testing additivity of treatment mixtures with chi-square analyses

AU - Pallmann, Philip

AU - Schaarschmidt, Frank

N1 - This is the peer reviewed version of the following article: Pallmann, P. and Schaarschmidt, F. (2015), Common pitfalls when testing additivity of treatment mixtures with chi-square analyses. Journal of Applied Entomology. 140: 135–141. doi: 10.1111/jen.12258 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jen.12258/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2016/2

Y1 - 2016/2

N2 - Studying interactions of multiple pesticides applied simultaneously in a mixture is a common task in phytopathology. Statistical methods are employed to test whether the treatment components influence each other's efficacy in a promotive or inhibitory way (synergistic or antagonistic interaction) or rather act independent of one another (additivity). The trouble is that widely used procedures based on chi-square tests are often seriously flawed, either because people apply them in a preposterous way or because the method simply does not fit the problem at hand. Browsing recent volumes of entomological journals, we found that numerous researchers have (in all likelihood unwittingly) analysed their data as if they had had a sample size of 100 or, equally bad, a sample size of one! We show how to avoid such poor practices and further argue that chi-square testing is, even if applied correctly (meaning that no technical errors are made), a limited purpose tool for assessing treatment interactions.

AB - Studying interactions of multiple pesticides applied simultaneously in a mixture is a common task in phytopathology. Statistical methods are employed to test whether the treatment components influence each other's efficacy in a promotive or inhibitory way (synergistic or antagonistic interaction) or rather act independent of one another (additivity). The trouble is that widely used procedures based on chi-square tests are often seriously flawed, either because people apply them in a preposterous way or because the method simply does not fit the problem at hand. Browsing recent volumes of entomological journals, we found that numerous researchers have (in all likelihood unwittingly) analysed their data as if they had had a sample size of 100 or, equally bad, a sample size of one! We show how to avoid such poor practices and further argue that chi-square testing is, even if applied correctly (meaning that no technical errors are made), a limited purpose tool for assessing treatment interactions.

KW - antagonism

KW - integrated pest management

KW - interaction

KW - statistical analysis

KW - synergism

U2 - 10.1111/jen.12258

DO - 10.1111/jen.12258

M3 - Journal article

VL - 140

SP - 135

EP - 141

JO - Journal of Applied Entomology

JF - Journal of Applied Entomology

SN - 0931-2048

IS - 1-2

ER -