Kosuke Imai, Michael Lingzhi Li
arXiv 10 Feb 2025 · Statistics — Methodology
arXiv:2502.06758 · PDF · DOI · OpenAlex · Extracted main text
We analyze the split-sample robust inference (SSRI) methodology proposed by Chernozhukov, Demirer, Duflo, and Fernandez-Val (CDDF) for quantifying uncertainty in heterogeneous treatment effect estimation. While SSRI effectively accounts for randomness in data splitting, its computational cost can be prohibitive when combined with complex machine learning (ML) models. We present an alternative randomization inference (RI) approach that maintains SSRI's generality without requiring repeated data splitting. By leveraging cross-fitting and design-based inference, RI achieves valid confidence intervals while significantly reducing computational burden. We compare the two methods through simulation, demonstrating that RI retains statistical efficiency while being more practical for large-scale applications.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Imai, K. and Li, M. L (2022) Statistical inference for heterogeneous treatment effects discovered by generic machine learning in randomized experiments self | 0.693 | 5 | 1 | 100% |
| 2 | Dorie, V., Hill, J., Shalit, U., Scott, M., and Cervone, D (2019) Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition | 0.405 | 1 | 1 | 100% |
| 3 | Li, M. L., Imai, K., Li, J., and Yang, X (2023) evalITR: evaluating individualized treatment rules self | 0.405 | 1 | 1 | 100% |
| 4 | Imai, K. and Li, M. L (2023) Experimental evaluation of individualized treatment rules self | 0.405 | 1 | 1 | 100% |
| 5 | Nadeau, C. and Bengio, Y (2000) Inference for the generalization error | 0.405 | 1 | 1 | 100% |
| 6 | Neyman, J (1923) On the application of probability theory to agricultural experiments: Essay on principles, section 9. (translated in 1990) | 0.405 | 1 | 1 | 100% |
Showing the top 6 of 6 scored citations.