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Statistical Significance

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...

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Are experiment sample sizes adequate to detect biologically important interactions between multiple stressors?

Benjamin J Burgess^1,2, Michelle C Jackson³, David J Murrell¹

¹Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment University College London London UK.

Ecology and Evolution

|September 30, 2022

Summary

Most ecosystem stressor interaction studies lack sufficient sample sizes to detect meaningful results. Researchers need at least 20 replicates per treatment to reliably identify non-additive stressor effects and avoid missing critical ecological interactions.

Keywords:

additive null model critical effect size ecosystem drivers experimental design minimum biological effect of interest multiplicative null model replicates statistical power

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Area of Science:

Ecology
Environmental Science
Statistical Biology

Background:

Ecosystems face multiple, co-occurring stressors, making it crucial to understand their interactive effects on biological responses.
Factorial experiments are commonly used to study stressor interactions, comparing observed responses to null model expectations.

Purpose of the Study:

To assess the adequacy of typical experimental sample sizes for detecting non-null stressor interaction responses.
To highlight the limitations of small sample sizes in ecological stressor interaction studies.

Main Methods:

Analysis of real and simulated data to evaluate statistical power with small sample sizes (typically <6 replicates).
Development of computer code to simulate data and estimate statistical power for user-defined responses and sample sizes under additive and multiplicative null models.

Main Results:

Small sample sizes (<6 replicates) can only detect very large deviations from additive null models, leading to the omission of many important stressor interactions.
Low power may result in the reporting of statistical outliers rather than genuine interaction effects.
Experiments likely require 20 or more replicates per treatment for adequate power to detect non-additive interactions.

Conclusions:

Current experimental practices often lack the statistical power to detect ecologically significant stressor interactions.
Accurate power estimation, considering the smallest biologically meaningful interaction, is essential for experimental design.
Increased sample sizes and careful consideration of statistical methods are needed to advance the understanding of ecosystem stressor interactions.