Estimating heterogeneous treatment effects (HTE) is crucial for identifying the variation of treatment effects across individuals or subgroups. Most ex- isting ...
Apr 24, 2023 · We propose a novel Stable CounterFactual Regression (StableCFR) to smooth the population distribution and upsample the underrepresented subpopulations.
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Jul 3, 2024 · Abstract:Heterogeneous treatment effect (HTE) estimation is vital for understanding the change of treatment effect across individuals or ...
Heterogeneous treatment effect (HTE) estimation is vital for understanding the change of treatment effect across individuals or subgroups.
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In this paper, we discuss a practical approach to studying heterogeneous treatment effects as a function of the treatment propensity.
Jul 23, 2023 · Abstract. Estimating heterogeneous treatment effects (HTE) is crucial for identifying the variation of treatment effects across individuals or ...
Jul 3, 2024 · This method minimizes the distribution distance between treated and control groups, effectively balancing confounders and producing similar ...
The main goals of HTE analysis are to estimate treatment effects in clinically relevant subgroups and to predict whether an individual might benefit from a ...
It is possible to search for heterogeneity in treatment effects simply by separately estimating cates us- ing many possible conditioning variables and ...
Heterogeneous treatment effect estimation is to quantify individual or subgroups' treatment effect by accounting for the heterogeneity of patient's conditions ...