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Do learning rates differ by race/ethnicity over kindergarten? Reconciling results across gain score, first-difference, and random effects models
ARTICLE

, Rossier School of Education, United States ; , Harvard Graduate School of Education, United States

Economics of Education Review Volume 59, Number 1, ISSN 0272-7757 Publisher: Elsevier Ltd

Abstract

The question of whether students’ school-year learning rates differ by race/ethnicity is important for monitoring educational inequality. Researchers applying different modeling strategies to the same data (the ECLS-K:99) have reached contrasting conclusions on this question. We outline the similarities and differences across three common approaches to estimating gains and heterogeneity in gains: 1) a gain score model (with intercept), 2) a first-difference (FD) model (in some cases equivalent to regression-through-the-origin [RTO] and student fixed effects models), and 3) a student random effects (RE) model. We show via simulation that FD/RTO and RE models produce estimates of learning rates – and group differences in learning rates – with more favorable RMSD compared to the gain score model with intercept. Using data from the ECLS-K:99, we demonstrate that these precision differences lead to contrasting inferences regarding learning rate heterogeneity, and likely explain the inconsistencies across previous studies.

Citation

Quinn, D.M. & McIntyre, J. (2017). Do learning rates differ by race/ethnicity over kindergarten? Reconciling results across gain score, first-difference, and random effects models. Economics of Education Review, 59(1), 81-86. Elsevier Ltd. Retrieved January 30, 2023 from .

This record was imported from Economics of Education Review on March 1, 2019. Economics of Education Review is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.econedurev.2017.06.006

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