Percentage Coefficient (bp) -- Effect Size Analysis (Theory Paper 1)
Xinshu Zhao (1), Dianshi Moses Li (2), Ze Zack Lai (1), Piper Liping, Liu (3), Song Harris Ao (1), Fei You (1) ((1) Department of Communication,, Faculty of Social Science, University of Macau, (2) Centre for Empirical, Legal Studies, Faculty of Law, University of Macau

TL;DR
This paper revisits the theory of the percentage coefficient (bp), an effect size estimator in regression analysis, emphasizing its interpretability and comparability on 0-1 percentage scales, and clarifying its role in measuring specific effect components.
Contribution
It provides a theoretical foundation for the percentage coefficient (bp), highlighting its advantages over other effect size indicators in terms of interpretability and comparison.
Findings
bp is interpretable on 0-1 percentage scales
bp effectively compares different estimands
bp measures the efficiency component of effect
Abstract
Percentage coefficient (bp) has emerged in recent publications as an additional and alternative estimator of effect size for regression analysis. This paper retraces the theory behind the estimator. It's posited that an estimator must first serve the fundamental function of enabling researchers and readers to comprehend an estimand, the target of estimation. It may then serve the instrumental function of enabling researchers and readers to compare two or more estimands. Defined as the regression coefficient when dependent variable (DV) and independent variable (IV) are both on conceptual 0-1 percentage scales, percentage coefficients (bp) feature 1) clearly comprehendible interpretation and 2) equitable scales for comparison. The coefficient (bp) serves the two functions effectively and efficiently. It thus serves needs unserved by other indicators, such as raw coefficient (bw) and…
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Taxonomy
TopicsStatistical Methods and Applications · Reliability and Agreement in Measurement · Advanced Statistical Methods and Models
