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SSDs Revisited: Part I-A Framework for Sample Size Guidance on Species Sensitivity Distribution Analysis.

G J Carr1, S E Belanger2

  • 1Data & Modeling Sciences, The Procter & Gamble Company, Mason, Ohio, USA.

Environmental Toxicology and Chemistry
|April 18, 2019
PubMed
Summary

This study introduces a sample size framework for species sensitivity distribution (SSD) analyses. Current SSD analyses are often adequately sized, but small sample sizes can lead to inaccurate hazardous concentration estimates.

Keywords:
BiostatisticsEcotoxicologyHazard/Risk AssessmentSpecies sensitivity distributions

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Area of Science:

  • Ecotoxicology
  • Environmental Chemistry
  • Statistical Modeling

Background:

  • Species sensitivity distribution (SSD) analyses are crucial for chemical safety assessments.
  • Determining appropriate sample sizes for SSD is essential for reliable statistical modeling.
  • Existing approaches lack a standardized framework for sample size determination.

Purpose of the Study:

  • To propose a comprehensive framework for sample size calculations in SSD analyses.
  • To evaluate the performance of current SSD analyses under various conditions.
  • To provide guidance for ensuring adequate statistical power in ecological risk assessments.

Main Methods:

  • Development of a framework applicable to Bayesian, frequentist, and nonparametric estimation methods.
  • Specification of statistical models and performance metrics for sample size analysis.
  • Simulation and analysis of current SSD practices with varying sample sizes and models.

Main Results:

  • The proposed framework offers a structured approach to sample size determination for SSD.
  • Many current SSD analyses appear adequately sized for estimating hazardous concentrations.
  • Estimates of hazardous concentrations can deviate significantly (over an order of magnitude) when sample sizes are small.

Conclusions:

  • The developed framework can guide stakeholders in chemical safety assessments towards appropriate sample sizes.
  • While many analyses are sufficient, attention to sample size is critical to avoid overestimation of chemical hazards.
  • Further agreement among stakeholders on representative models and performance criteria is needed for definitive guidance.