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A critique of current trends in the statistical analysis of seed germination and viability data

Published online by Cambridge University Press:  06 March 2012

Gudeta W. Sileshi
Gudeta W. Sileshi*
Affiliation:
World Agroforestry Centre (ICRAF), SADC-ICRAF Agroforestry Programme, PO Box 30798, Lilongwe, Malawi
*
*Correspondence Email: sgwelde@yahoo.com
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Abstract

Statistical analysis is increasingly used in seed germination/viability studies across different disciplines. The objective of this opinion piece is to assess current trends in statistical analysis of such data, and draw attention of readers to the limitations of the usual inferential statistics in controlling error rates. The assessments are based on a survey of 429 papers published in 139 peer-reviewed journals in the past 11 years. My intention is to identify areas of concern across a wide range of studies. Accordingly, the areas of greatest concern found in the analysis of percentage seed germination and viability data were: (1) pseudoreplication and/or use of a few replicates; (2) ignoring assumptions of ANOVA and non-parametric tests (NPARTs); (3) uncritical data transformation; (4) arbitrary choice of multiple comparison tests; and (5) lack of emphasis on effect sizes. Given the prevalence of these problems, in my opinion we would be building a body of knowledge on a shaky ground. The discussions that follow will: (1) describe situations where germination data violate assumptions of ANOVA and NPARTs; (2) highlight the implications of the various problems to Type I and Type II error rates; and (3) indicate remedial measures based on the recent statistical literature.

Keywords

ANOVAconservationfalse discovery rategeneralized linear mixed modelsgeneralized linear modelsinvasive alienspseudoreplication
Type
Research Opinion
Information
Seed Science Research , Volume 22 , Issue 3 , September 2012 , pp. 145 - 159
Copyright
Copyright © Cambridge University Press 2012

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