Equivalence testing in pesticide risk assessment: evaluation and practical guidance for design, analysis and interpretation
Year: 2026
Type: article
Abstract: experimental_allocation() is an R function for the balanced, randomised allocation of experimental units to treatments using anticlustering. It assigns subjects (e.g. bee colonies, plots, or other experimental units) to named treatments while balancing user-defined numeric covariates between the treatments, with a controllable number of replicates per treatment. When a data frame of groups within treatments is supplied via the group_data argument, subjects are additionally allocated to groups (e.g. sites, or blocks) within each treatment, again balancing the covariates. Internally, the function matches similar units into sets (via anticlust::matching()) and then distributes each set across the treatments (via anticlust::anticlustering()), so that similar units are spread across groups and the resulting groups resemble one another. The function requires the anticlust package (Papenberg & Klau, 2021). If you use this function, please cite the associated paper (Wintermantel et al.) and, where appropriate, the anticlust package. References: Wintermantel, D, Osterman, J., Mair, M, M., Hartig, F. (in preparation) Equivalence testing in pesticide risk assessment - Evaluation and practical guidance for design, analysis and interpretation. Papenberg, M., & Klau, G. W. (2021). Using anticlustering to partition data sets into equivalent parts. Psychological Methods, 26(2), 161–174. https://doi.org/10.1037/met0000301.
Source: Environment International
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $4,750
Funder: European Commission
OpenAlex ID: W7167014203
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