When assessing the effectiveness of a large-scale, federally funded program such as Head Start—a program designed to better prepare children ages 3-5 from low-income families for school—it is limited to only look at the Average Treatment Effect given the “considerable systematic heterogeneity within population between individuals.” This study applies complex variance modelling, an extension of multilevel modelling, to capture the variance, as well as the mean, in order to shed light on the heterogeneity in the treatment effects (HTE), and possibly better guide future policies and interventions.
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