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Estimating Heterogeneous Treatment Effects with Item-Level Outcome Data: Insights from Item Response Theory
Our results show that the IL-HTE model reveals item-level variation masked by average treatment effects, provides more accurate statistical inference, allows for estimates of the generalizability of causal effects, resolves identification problems in the estimation of interaction effects, and provides estimates of standardized treatment effect sizes corrected for attenuation due to measurement error.
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