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May 8, 2026Open Access

Standardizing predictors for effect size measures in multilevel modeling with random slopes and sampling weights

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Authors

GCGuanyu Chen

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Overview

Randomized trial evaluates effect size measures in multilevel models with random slopes, suggesting improved calculations and standards.

Key Points

  • This dissertation aims to standardize effect size measures in multilevel modeling, focusing on random slopes and sampling weights.
  • Conducted a review of effect size reporting practices based on a survey of four academic journals.
  • Developed a predictor standardization approach and compared it with Johnson’s mixture distribution approach.
  • Extended effect size measures to incorporate sampling weights for better population-level inference.
  • Both the predictor standardization approach and Johnson’s method provided effect sizes close to true values in simulations.
  • Illustrated that standardizing predictors simplifies computation of effect sizes like R² and standardized mean differences.
  • Provided empirical examples showing practical application of the new methods.

Cite This Study

Guanyu Chen (2026) studied this question.

synapsesocial.com/papers/69fd7e79bfa21ec5bbf06ba8https://doi.org/10.14288/1.0452058
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