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Full Matching in an Observational Study of Coaching for the SAT

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Cited by:

  1. David Kaplan & Jianshen Chen, 2012. "A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 581-609, July.
  2. Hess, Sebastian & Bolos, Laura A. & Hoffmann, Ruben & Surry, Yves, 2014. "Is animal welfare better on small farms? Evidence from veterinary inspections on Swedish farms," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182781, European Association of Agricultural Economists.
  3. Boulding, Carew & Wampler, Brian, 2010. "Voice, Votes, and Resources: Evaluating the Effect of Participatory Democracy on Well-being," World Development, Elsevier, vol. 38(1), pages 125-135, January.
  4. Phuong Nguyen-Hoang, 2012. "Fiscal effects of budget referendums: evidence from New York school districts," Public Choice, Springer, vol. 150(1), pages 77-95, January.
  5. repec:jss:jstsof:25:i11 is not listed on IDEAS
  6. Colin B. Fogarty & Mark E. Mikkelsen & David F. Gaieski & Dylan S. Small, 2016. "Discrete Optimization for Interpretable Study Populations and Randomization Inference in an Observational Study of Severe Sepsis Mortality," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 447-458, April.
  7. Lenis, David & Ackerman, Benjamin & Stuart, Elizabeth A., 2018. "Measuring model misspecification: Application to propensity score methods with complex survey data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 48-57.
  8. Alberto Abadie & Guido W. Imbens, 2012. "A Martingale Representation for Matching Estimators," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 833-843, June.
  9. Prashant Loyalka & Andrey Zakharov, 2014. "Does shadow education help students prepare for college?," HSE Working papers WP BRP 15/EDU/2014, National Research University Higher School of Economics.
  10. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
  11. Tom Fangyun Tan & Serguei Netessine, 2020. "At Your Service on the Table: Impact of Tabletop Technology on Restaurant Performance," Management Science, INFORMS, vol. 66(10), pages 4496-4515, October.
  12. Martin Cousineau & Vedat Verter & Susan A. Murphy & Joelle Pineau, 2022. "Estimating causal effects with optimization-based methods: A review and empirical comparison," Papers 2203.00097, arXiv.org.
  13. Nicole E. Pashley & Luke W. Miratrix, 2021. "Insights on Variance Estimation for Blocked and Matched Pairs Designs," Journal of Educational and Behavioral Statistics, , vol. 46(3), pages 271-296, June.
  14. Zhenzhen Xu & John D. Kalbfleisch, 2010. "Propensity Score Matching in Randomized Clinical Trials," Biometrics, The International Biometric Society, vol. 66(3), pages 813-823, September.
  15. Gonzalez-Ramirez, Maria Jimena & Kling, Catherine L. & Arbuckle, J. Gordon Jr., 2015. "Cost-share Effectiveness in the Adoption of Cover Crops in Iowa," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205876, Agricultural and Applied Economics Association.
  16. Siyu Heng & Hyunseung Kang & Dylan S. Small & Colin B. Fogarty, 2021. "Increasing power for observational studies of aberrant response: An adaptive approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 482-504, July.
  17. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
  18. Naina J Ahuja & Allison Nguyen & Sandra J Winter & Mark Freeman & Robert Shi & Patricia Rodriguez Espinosa & Catherine A Heaney, 2020. "Well-Being without a Roof: Examining Well-Being among Unhoused Individuals Using Mixed Methods and Propensity Score Matching," IJERPH, MDPI, vol. 17(19), pages 1-13, October.
  19. Stephen L. Morgan & David J. Harding, 2006. "Matching Estimators of Causal Effects," Sociological Methods & Research, , vol. 35(1), pages 3-60, August.
  20. Guccio, Calogero & Pignataro, Giacomo & Romeo, Domenica & Vidoli, Francesco, 2024. "Is austerity good for efficiency, at least? A counterfactual assessment for the Italian NHS," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
  21. Ghosh, Debashis, 2011. "Propensity score modelling in observational studies using dimension reduction methods," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 813-820, July.
  22. Colin B. Fogarty & Pixu Shi & Mark E. Mikkelsen & Dylan S. Small, 2017. "Randomization Inference and Sensitivity Analysis for Composite Null Hypotheses With Binary Outcomes in Matched Observational Studies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 321-331, January.
  23. Zhenzhen Xu & John D. Kalbfleisch, 2013. "Repeated Randomization and Matching in Multi-Arm Trials," Biometrics, The International Biometric Society, vol. 69(4), pages 949-959, December.
  24. Loyalka, Prashant & Zakharov, Andrey, 2016. "Does shadow education help students prepare for college? Evidence from Russia," International Journal of Educational Development, Elsevier, vol. 49(C), pages 22-30.
  25. Iacus, Stefano & Porro, Giuseppe, 2008. "Invariant and Metric Free Proximities for Data Matching: An R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i11).
  26. Gerrie‐Cor Herber & Maarten Schipper & Marc Koopmanschap & Karin Proper & Fons van der Lucht & Hendriek Boshuizen & Johan Polder & Ellen Uiters, 2020. "Health expenditure of employees versus self‐employed individuals; a 5 year study," Health Economics, John Wiley & Sons, Ltd., vol. 29(12), pages 1606-1619, December.
  27. Frimpong, Eugene & Petrolia, Daniel, 2016. "Community-level Flood Mitigation Effects on Household Flood Insurance and Damage Claims," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230129, Southern Agricultural Economics Association.
  28. Colin B. Fogarty, 2023. "Testing weak nulls in matched observational studies," Biometrics, The International Biometric Society, vol. 79(3), pages 2196-2207, September.
  29. Odis Johnson Jr. & Michael Wagner, 2017. "Equalizers or Enablers of Inequality? A Counterfactual Analysis of Racial and Residential Test Score Gaps in Year-Round and Nine-Month Schools," The ANNALS of the American Academy of Political and Social Science, , vol. 674(1), pages 240-261, November.
  30. Raiden B. Hasegawa & Sameer K. Deshpande & Dylan S. Small & Paul R. Rosenbaum, 2020. "Causal Inference With Two Versions of Treatment," Journal of Educational and Behavioral Statistics, , vol. 45(4), pages 426-445, August.
  31. Nattino, Giovanni & Song, Chi & Lu, Bo, 2022. "Polymatching algorithm in observational studies with multiple treatment groups," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
  32. Jason Lyall, 2008. "Does Indiscriminate Violence Incite Insurgent Attacks? Evidence from a Natural Experiment," HiCN Working Papers 44, Households in Conflict Network.
  33. 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.
  34. Loh, Wen Wei & Ren, Dongning, 2021. "Data-driven Covariate Selection for Confounding Adjustment by Focusing on the Stability of the Effect Estimator," OSF Preprints yve6u, Center for Open Science.
  35. Stephanie L Mayne & Brian K Lee & Amy H Auchincloss, 2015. "Evaluating Propensity Score Methods in a Quasi-Experimental Study of the Impact of Menu-Labeling," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-12, December.
  36. Bo Zhang & Dylan S. Small, 2020. "A calibrated sensitivity analysis for matched observational studies with application to the effect of second‐hand smoke exposure on blood lead levels in children," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1285-1305, November.
  37. Glazer Amanda K. & Pimentel Samuel D., 2023. "Robust inference for matching under rolling enrollment," Journal of Causal Inference, De Gruyter, vol. 11(1), pages 1-19, January.
  38. Casey A. Klofstad & Benjamin G. Bishin, 2014. "Do Social Ties Encourage Immigrant Voters to Participate in Other Campaign Activities?," Social Science Quarterly, Southwestern Social Science Association, vol. 95(2), pages 295-310, June.
  39. Libo Sun & Guodong Lyu & Yugang Yu & Chung‐Piaw Teo, 2020. "Fulfillment by Amazon versus fulfillment by seller: An interpretable risk‐adjusted fulfillment model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 627-645, December.
  40. Jennings, Wesley G. & Richards, Tara N. & Dwayne Smith, M. & Bjerregaard, Beth & Fogel, Sondra J., 2014. "A Critical Examination of the “White Victim Effect” and Death Penalty Decision-Making from a Propensity Score Matching Approach: The North Carolina Experience," Journal of Criminal Justice, Elsevier, vol. 42(5), pages 384-398.
  41. Richard Aviles-Lopez & Juan de Dios Luna del Castillo & Miguel Ángel Montero-Alonso, 2023. "Exploratory Matching Model Search Algorithm (EMMSA) for Causal Analysis: Application to the Cardboard Industry," Mathematics, MDPI, vol. 11(21), pages 1-34, October.
  42. Daniele Bottigliengo & Giulia Lorenzoni & Honoria Ocagli & Matteo Martinato & Paola Berchialla & Dario Gregori, 2021. "Propensity Score Analysis with Partially Observed Baseline Covariates: A Practical Comparison of Methods for Handling Missing Data," IJERPH, MDPI, vol. 18(13), pages 1-17, June.
  43. Cousineau, Martin & Verter, Vedat & Murphy, Susan A. & Pineau, Joelle, 2023. "Estimating causal effects with optimization-based methods: A review and empirical comparison," European Journal of Operational Research, Elsevier, vol. 304(2), pages 367-380.
  44. José R. Zubizarreta, 2012. "Using Mixed Integer Programming for Matching in an Observational Study of Kidney Failure After Surgery," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1360-1371, December.
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