Optimal Multilevel Matching in Clustered Observational Studies: A Case Study of the Effectiveness of Private Schools Under a Large-Scale Voucher System
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DOI: 10.1080/01621459.2016.1240683
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Cited by:
- Youjin Lee & Trang Q. Nguyen & Elizabeth A. Stuart, 2021. "Partially pooled propensity score models for average treatment effect estimation with multilevel data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1578-1598, October.
- Fatih Unlu & Douglas Lee Lauen & Sarah Crittenden Fuller & Tiffany Berglund & Elc Estrera, 2021. "Can Quasi‐Experimental Evaluations That Rely On State Longitudinal Data Systems Replicate Experimental Results?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(2), pages 572-613, March.
- Md Saiful Islam & Md Sarowar Morshed & Gary J Young & Md Noor-E-Alam, 2019. "Robust policy evaluation from large-scale observational studies," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-19, October.
- Bikram Karmakar, 2022. "An approximation algorithm for blocking of an experimental design," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1726-1750, November.
- Aleksey Oshchepkov & Anna Shirokanova, 2020. "Multilevel Modeling For Economists: Why, When And How," HSE Working papers WP BRP 233/EC/2020, National Research University Higher School of Economics.
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