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Evaluating Kindergarten Retention Policy: A Case Study of Causal Inference for Multilevel Observational Data

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  1. 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.
  2. Yongyun Shin & Stephen W. Raudenbush, 2011. "The Causal Effect of Class Size on Academic Achievement," Journal of Educational and Behavioral Statistics, , vol. 36(2), pages 154-185, April.
  3. Benjamin Kelcey & Nianbo Dong & Jessaca Spybrook & Kyle Cox, 2017. "Statistical Power for Causally Defined Indirect Effects in Group-Randomized Trials With Individual-Level Mediators," Journal of Educational and Behavioral Statistics, , vol. 42(5), pages 499-530, October.
  4. Peter Z. Schochet, "undated". "Statistical Theory for the RCT-YES Software: Design-Based Causal Inference for RCTs," Mathematica Policy Research Reports a0c005c003c242308a92c02dc, Mathematica Policy Research.
  5. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
  6. Bryan Keller & Elizabeth Tipton, 2016. "Propensity Score Analysis in R," Journal of Educational and Behavioral Statistics, , vol. 41(3), pages 326-348, June.
  7. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
  8. Joana Pipa & Francisco Peixoto, 2022. "One Step Back or One Step Forward? Effects of Grade Retention and School Retention Composition on Portuguese Students’ Psychosocial Outcomes Using PISA 2018 Data," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
  9. Xu Qin & Jonah Deutsch & Guanglei Hong, 2021. "Unpacking Complex Mediation Mechanisms And Their Heterogeneity Between Sites In A Job Corps Evaluation," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 40(1), pages 158-190, January.
  10. Luke Keele & Rocío Titiunik, 2018. "Geographic Natural Experiments with Interference: The Effect of All-Mail Voting on Turnout in Colorado," CESifo Economic Studies, CESifo Group, vol. 64(2), pages 127-149.
  11. Xu Qin & Guanglei Hong, 2017. "A Weighting Method for Assessing Between-Site Heterogeneity in Causal Mediation Mechanism," Journal of Educational and Behavioral Statistics, , vol. 42(3), pages 308-340, June.
  12. Laura Forastiere & Patrizia Lattarulo & Marco Mariani & Fabrizia Mealli & Laura Razzolini, 2021. "Exploring Encouragement, Treatment, and Spillover Effects Using Principal Stratification, With Application to a Field Experiment on Teens’ Museum Attendance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 244-258, January.
  13. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
  14. Tadao Hoshino & Takahide Yanagi, 2023. "Randomization Test for the Specification of Interference Structure," Papers 2301.05580, arXiv.org, revised Dec 2023.
  15. Chiba, Yasutaka, 2012. "A note on bounds for the causal infectiousness effect in vaccine trials," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1422-1429.
  16. Robert Minton & Casey B. Mulligan, 2024. "Difference-in-Differences in the Marketplace," Finance and Economics Discussion Series 2024-008, Board of Governors of the Federal Reserve System (U.S.).
  17. Nianbo Dong & Mark W. Lipsey, 2018. "Can Propensity Score Analysis Approximate Randomized Experiments Using Pretest and Demographic Information in Pre-K Intervention Research?," Evaluation Review, , vol. 42(1), pages 34-70, February.
  18. Peter Z. Schochet, 2013. "Student Mobility, Dosage, and Principal Stratification in School-Based RCTs," Journal of Educational and Behavioral Statistics, , vol. 38(4), pages 323-354, August.
  19. Weicong Lyu & Jee-Seon Kim & Youmi Suk, 2023. "Estimating Heterogeneous Treatment Effects Within Latent Class Multilevel Models: A Bayesian Approach," Journal of Educational and Behavioral Statistics, , vol. 48(1), pages 3-36, February.
  20. Rigdon, Joseph & Hudgens, Michael G., 2015. "Exact confidence intervals in the presence of interference," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 130-135.
  21. J. R. Lockwood & D. McCaffrey, 2020. "Using hidden information and performance level boundaries to study student–teacher assignments: implications for estimating teacher causal effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1333-1362, October.
  22. Youmi Suk & Jee-Seon Kim & Hyunseung Kang, 2021. "Hybridizing Machine Learning Methods and Finite Mixture Models for Estimating Heterogeneous Treatment Effects in Latent Classes," Journal of Educational and Behavioral Statistics, , vol. 46(3), pages 323-347, June.
  23. Arpino, Bruno & Mealli, Fabrizia, 2011. "The specification of the propensity score in multilevel observational studies," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1770-1780, April.
  24. Tadao Hoshino & Takahide Yanagi, 2021. "Causal Inference with Noncompliance and Unknown Interference," Papers 2108.07455, arXiv.org, revised Oct 2023.
  25. Silvia Noirjean & Marco Mariani & Alessandra Mattei & Fabrizia Mealli, 2020. "Exploiting network information to disentangle spillover effects in a field experiment on teens' museum attendance," Papers 2011.11023, arXiv.org, revised May 2022.
  26. Nicholas A. Bowman & KC Culver, 2018. "When Do Honors Programs Make the Grade? Conditional Effects on College Satisfaction, Achievement, Retention, and Graduation," Research in Higher Education, Springer;Association for Institutional Research, vol. 59(3), pages 249-272, May.
  27. Mäkinen, Taneli & Li, Fan & Mercatanti, Andrea & Silvestrini, Andrea, 2022. "Causal analysis of central bank holdings of corporate bonds under interference," Economic Modelling, Elsevier, vol. 113(C).
  28. Youmi Suk & Kyung T. Han, 2024. "A Psychometric Framework for Evaluating Fairness in Algorithmic Decision Making: Differential Algorithmic Functioning," Journal of Educational and Behavioral Statistics, , vol. 49(2), pages 151-172, April.
  29. Mary Ying-Fang Wang & Paul Tuss & Lihong Qi, 2019. "Augmented Weighted Estimators Dealing with Practical Positivity Violation to Causal inferences in a Random Coefficient Model," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 447-467, June.
  30. Arpino, Bruno & Mattei, Alessandra, 2013. "Assessing the Impact of Financial Aids to Firms: Causal Inference in the presence of Interference," MPRA Paper 51795, University Library of Munich, Germany.
  31. 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.
  32. Lindsay C. Page, 2012. "Understanding the Impact of Career Academy Attendance," Evaluation Review, , vol. 36(2), pages 99-132, April.
  33. Youmi Suk & Hyunseung Kang, 2022. "Robust Machine Learning for Treatment Effects in Multilevel Observational Studies Under Cluster-level Unmeasured Confounding," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 310-343, March.
  34. VanderWeele Tyler J. & Hernan Miguel A., 2013. "Causal inference under multiple versions of treatment," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 1-20, June.
  35. Elizabeth Tipton, 2013. "Improving Generalizations From Experiments Using Propensity Score Subclassification," Journal of Educational and Behavioral Statistics, , vol. 38(3), pages 239-266, June.
  36. Nianbo Dong & Elizabeth A. Stuart & David Lenis & Trang Quynh Nguyen, 2020. "Using Propensity Score Analysis of Survey Data to Estimate Population Average Treatment Effects: A Case Study Comparing Different Methods," Evaluation Review, , vol. 44(1), pages 84-108, February.
  37. VanderWeele, Tyler J. & Tchetgen Tchetgen, Eric J., 2011. "Effect partitioning under interference in two-stage randomized vaccine trials," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 861-869, July.
  38. Keenan A. Pituch & Laura M. Stapleton, 2012. "Distinguishing Between Cross- and Cluster-Level Mediation Processes in the Cluster Randomized Trial," Sociological Methods & Research, , vol. 41(4), pages 630-670, November.
  39. Tyler J. VanderWeele, 2010. "Direct and Indirect Effects for Neighborhood-Based Clustered and Longitudinal Data," Sociological Methods & Research, , vol. 38(4), pages 515-544, May.
  40. Yongyun Shin, 2012. "Do Black Children Benefit More From Small Classes? Multivariate Instrumental Variable Estimators With Ignorable Missing Data," Journal of Educational and Behavioral Statistics, , vol. 37(4), pages 543-574, August.
  41. Soojin Park & Peter M. Steiner & David Kaplan, 2018. "Identification and Sensitivity Analysis for Average Causal Mediation Effects with Time-Varying Treatments and Mediators: Investigating the Underlying Mechanisms of Kindergarten Retention Policy," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 298-320, June.
  42. KOGURE, Katsuo & 小暮, 克夫, 2017. "Some Remarks on the Causal Inference for Historical Persistence," Discussion paper series HIAS-E-44, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
  43. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.
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