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Regression modelQuasi-experimental / causal inference

Ukadiriaji Imara Mara Mbili wa Athari Tofauti za Matibabu

Ukadiriaji imara mara mbili wa athari tofauti za matibabu (HTE) hukadiria jinsi athari ya kisababishi ya matibabu inavyotofautiana katika vikundi vidogo au thamani za vigezo vya mtu binafsi. Kwa kuchanganya mfumo wa matokeo na mfumo wa alama za mwelekeo, unadumisha uthabiti ikiwa mojawapo ya mifumo imebainishwa kwa usahihi, na inasaidia wakadiriaji wa usumbufu wa kujifunza kwa mashine wanaonyumbulika kupitia ukadiriaji-mtambuka ili kutoa makadirio halali ya athari ya wastani ya matibabu yenye masharti (CATE).

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Vyanzo

  1. Kennedy, E. H. (2023). Towards optimal doubly robust estimation of heterogeneous causal effects. Electronic Journal of Statistics, 17(2), 3008-3049. DOI: 10.1214/23-EJS2157
  2. Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., & Robins, J. (2018). Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21(1), C1-C68. DOI: 10.1111/ectj.12097

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Doubly Robust Estimation of Heterogeneous Treatment Effects. ScholarGate. https://scholargate.app/sw/causal-inference/heterogeneous-treatment-effect-doubly-robust-estimation

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ScholarGateHeterogeneous treatment effect Doubly robust estimation (Doubly Robust Estimation of Heterogeneous Treatment Effects). Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/causal-inference/heterogeneous-treatment-effect-doubly-robust-estimation · Seti ya data: https://doi.org/10.5281/zenodo.20539026