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Regression modelQuasi-experimental / causal inference

Ubunifu wa kifani ulioimarishwa na akili bandia

Ubunifu wa kifani ulioimarishwa na akili bandia unachanganya mfumo wa kawaida wa kifani—ambao hufuatilia mienendo ya matokeo karibu na tarehe ya matibabu—na mbinu za msingi wa akili bandia kama vile akili bandia maradufu/iliyofutwa (DML) au urejeshaji uliowekwa alama ili kushughulikia vigezo vingi, kuboresha udhibiti wa vishawishi, na kutoa makadirio halali ya sababu wakati nafasi ya kigezo ni kubwa sana kwa urejeshaji wa kawaida kuweza kudhibiti kwa uaminifu.

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Vyanzo

  1. 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
  2. Athey, S., & Imbens, G. W. (2022). Design-based analysis in difference-in-differences settings with staggered adoption. Journal of Econometrics, 226(1), 62-79. DOI: 10.1016/j.jeconom.2020.10.012

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Machine Learning-Augmented Event Study Design. ScholarGate. https://scholargate.app/sw/causal-inference/machine-learning-augmented-event-study-design

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ScholarGateMachine learning-augmented event study design (Machine Learning-Augmented Event Study Design). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/causal-inference/machine-learning-augmented-event-study-design · Seti ya data: https://doi.org/10.5281/zenodo.20539026