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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

Daiki Nakamura

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2 papers indexed here

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Sep 2026

The denominator chooses the estimand: A target-population true-score framework for standardized mean differences.

The standardized mean difference (SMD) is a workhorse effect-size index across psychology, education, and the behavioral sciences, but its denominator embeds estimand-level commitments-about reliability, sample heterogeneity, and the reference scale on which the effect is interpreted-that are rarely made explicit. We t...

Daiki Nakamura · 0 citations
Sep 2026

Kurtosis-robust estimation of the fixed effects eta-squared: An impossibility theorem for F-based estimators and a practical correction.

Eta-squared (η2) is the most widely reported proportion-of-variance effect size in ANOVA, yet its estimators are biased and non-normality is rarely studied. We prove that, for balanced one-way fixed effects ANOVA, no function of the usual F-statistic-the class containing the estimators in routine use-is exactly unbiase...

Daiki Nakamura · 0 citations

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