Gifted and talented services for EFL learners in China: A step-by-step guide to propensity score matching analysis in R

Abstract

We sought to quantify the effectiveness of a gifted and talented (GT) program, as was provided to university students who demonstrated a talent for learning English as a foreign language (EFL) in China. To do so, we used propensity score matching (PSM) techniques to analyze data collected from a tier-1 university where an English talent (ET) program was provided. Specifically, we provided (a) a step-by-step guide of PSM analysis using the R analytical package, (b) the codes for PSM analysis and visualization, and (c) the final analysis of baseline equivalence and treatment effect based on the matching sample. Collectively, the results of descriptive statistics, visualization, and baseline equivalence indicate that PSM is an effective matching technique for generating an unbiased counterfactual analysis. Moreover, the ET program yields a statistically significant, positive effect on ET students’ English language proficiency.