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Efficiency Study of Estimators for a Treatment Effect in a Pretest-Posttest Trial

Citations

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Cited by:

  1. Yujia Gu & Hanzhong Liu & Wei Ma, 2023. "Regression‐based multiple treatment effect estimation under covariate‐adaptive randomization," Biometrics, The International Biometric Society, vol. 79(4), pages 2869-2880, December.
  2. 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.
  3. Pierre Chausse & George Luta, 2017. "Casual Inference using Generalized Empirical Likelihood Methods," Working Papers 1707, University of Waterloo, Department of Economics, revised Dec 2017.
  4. Peter Z. Schochet, 2018. "Design-Based Estimators for Average Treatment Effects for Multi-Armed RCTs," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 568-593, October.
  5. Peter Z. Schochet, "undated". "The Late Pretest Problem in Randomized Control Trials of Education Interventions," Mathematica Policy Research Reports fb514df5dbb84a5dbea79865c, Mathematica Policy Research.
  6. Jinkook Lee & Drystan Phillips, 2011. "Income and Poverty among Older Koreans Relative Contributions of and Relationship between Public and Family Transfers," Working Papers WR-852, RAND Corporation.
  7. Azzam, Tarek & Bates, Michael D. & Fairris, David, 2022. "Do learning communities increase first year college retention? Evidence from a randomized control trial," Economics of Education Review, Elsevier, vol. 89(C).
  8. David Benkeser & Iván Díaz & Alex Luedtke & Jodi Segal & Daniel Scharfstein & Michael Rosenblum, 2021. "Improving precision and power in randomized trials for COVID‐19 treatments using covariate adjustment, for binary, ordinal, and time‐to‐event outcomes," Biometrics, The International Biometric Society, vol. 77(4), pages 1467-1481, December.
  9. repec:mpr:mprres:5699 is not listed on IDEAS
  10. Jitendra Ganju, 2004. "Some Unexamined Aspects of Analysis of Covariance in Pretest–Posttest Studies," Biometrics, The International Biometric Society, vol. 60(3), pages 829-833, September.
  11. Bai, Yuehao & Jiang, Liang & Romano, Joseph P. & Shaikh, Azeem M. & Zhang, Yichong, 2024. "Covariate adjustment in experiments with matched pairs," Journal of Econometrics, Elsevier, vol. 241(1).
  12. John A. List & Azeem M. Shaikh & Atom Vayalinkal, 2023. "Multiple testing with covariate adjustment in experimental economics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 920-939, September.
  13. J. R. Lockwood & Daniel F. McCaffrey, 2019. "Impact Evaluation Using Analysis of Covariance With Error-Prone Covariates That Violate Surrogacy," Evaluation Review, , vol. 43(6), pages 335-369, December.
  14. Peter Z. Schochet, 2013. "Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference," Journal of Educational and Behavioral Statistics, , vol. 38(3), pages 219-238, June.
  15. Jonathan W. Bartlett, 2020. "Robustness of ANCOVA in randomized trials with unequal randomization," Biometrics, The International Biometric Society, vol. 76(3), pages 1036-1038, September.
  16. Rosenblum Michael & van der Laan Mark J., 2010. "Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-44, April.
  17. Undral Byambadalai & Tatsushi Oka & Shota Yasui, 2024. "Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction," Papers 2407.16037, arXiv.org.
  18. Donald P. Green & Winston Lin & Claudia Gerber, 2018. "Optimal Allocation of Interviews to Baseline and Endline Surveys in Place-Based Randomized Trials and Quasi-Experiments," Evaluation Review, , vol. 42(4), pages 391-422, August.
  19. Peter Z. Schochet, 2020. "Analyzing Grouped Administrative Data for RCTs Using Design-Based Methods," Journal of Educational and Behavioral Statistics, , vol. 45(1), pages 32-57, February.
  20. Selene Leon & Anastasios A. Tsiatis & Marie Davidian, 2003. "Semiparametric Estimation of Treatment Effect in a Pretest-Posttest Study," Biometrics, The International Biometric Society, vol. 59(4), pages 1046-1055, December.
  21. Min Zhang & Anastasios A. Tsiatis & Marie Davidian, 2008. "Improving Efficiency of Inferences in Randomized Clinical Trials Using Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 64(3), pages 707-715, September.
  22. Peter Z. Schochet, "undated". "Technical Methods Report: Statistical Power for Regression Discontinuity Designs in Education Evaluations," Mathematica Policy Research Reports 61fb6c057561451a8a6074508, Mathematica Policy Research.
  23. repec:mpr:mprres:6372 is not listed on IDEAS
  24. repec:mpr:mprres:6094 is not listed on IDEAS
  25. Peter Z. Schochet, 2010. "The Late Pretest Problem in Randomized Control Trials of Education Interventions," Journal of Educational and Behavioral Statistics, , vol. 35(4), pages 379-406, August.
  26. Nicholas Williams & Michael Rosenblum & Iván Díaz, 2022. "Optimising precision and power by machine learning in randomised trials with ordinal and time‐to‐event outcomes with an application to COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2156-2178, October.
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