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June 6, 2026Open Veterinary JournalOpen Access

Relative importance analysis of correlated predictors in aquatic veterinary science: Application to an abalone dataset

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Authors

EMElmabrok MasaoudASAbulwahid SirtiyahMAMohammed Abdulqadir

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Overview

Randomized trial finds shell weight is the dominant predictor for ring count in abalone, suggesting effective analytical methods.

Key Points

  • The aim is to introduce statistical approaches for quantifying relative importance of correlated predictors in veterinary science.
  • Evaluated statistical approaches for predictor importance in R software.
  • Assessed methods include Shapley value-based decomposition, Genizi method, relative weights analysis, and dominance analysis.
  • Applied analysis to an abalone dataset focusing on predictors relevant to age estimation.
  • Shell weight ranked as the most influential predictor for ring count (proxy for age) consistently across all methods.
  • Genizi method provided clear separation among predictors while PMVD metric showed overlapping importance.
  • Relative weights and Genizi method yielded narrow confidence intervals, indicating robust estimates compared to PMVD metrics.

Cite This Study

Masaoud et al. (2026) studied this question.

synapsesocial.com/papers/6a23b83e71a5da9775e747b3https://doi.org/10.5455/ovj.2026.v16.i5.55
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