r2_mlm: A command for computing R-squared measures for models fit by mixed

Anthony J. Gambino () and D. Betsy McCoach ()
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Anthony J. Gambino: University of Connecticut
D. Betsy McCoach: Fordham University

Stata Journal, 2025, vol. 25, issue 4, 719-742

Abstract: The article by Rights and Sterba (2023, Multivariate Behavioral Research 58: 340–367) provides a comprehensive framework for computing R2 measures for (linear) multilevel models. In this article, we introduce r2_mlm, a postestimation command for mixed that computes R2 measures using Rights and Sterba’s framework. We explain how this R2 framework works and demonstrate how r2_mlm can be used to compute various R2 measures for models fit by mixed. One of the most useful features of r2_mlm is that it will produce warning messages if the user specifies the model in a way that may lead to conflation bias (an easily overlooked issue). Finally, we walk through a simple example and explain how to interpret the various R2 measures.

Keywords: r2_mlm; mixed; multilevel modeling; explained variation; R2; conflation bias (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1177/1536867X251398326

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