- Disclosure
- List of Tables & Figures
- Chapter 1. Introduction
- Chapter 2. The Late Pretest Problem
- Chapter 3. Measuring the Variance-Bias Tradeoff
- Chapter 4. Considered Designs
- Chapter 5. Theoretical Framework
- Chapter 6. The Variance-Bias Tradeoff for Various ATE Estimators
- Chapter 7: Empirical Analysis
- Chapter 8: Summary and Conclusions
- References
Appendix A: Proof of Asymptotic Results for the ANCOVA Estimator (174 KB)- PDF & Related Info
Chapter 8: Summary and Conclusions
References
Allison, P. (1990). Change Scores as Dependent Variables in Regression Analysis. In Sociological Methodology (20). Edited by C. Clogg. Oxford, UK: Blackwell, 93-114;
Bloom, H., L. Hayes, and A. Black (2005). Using Covariates to Improve Precision. New York, NY: MDRC.
Byrk, A. and S. Raudenbush (1992). Hierarchical Linear Models for Social and Behavioral Research. Applications and Data Analysis Methods. Newbury Park, CA: Sage.
Cochran, W. (1963). Sampling Techniques. New York: John Wiley and Sons.
Cohen, J. (1988). Statistical Power Analysis for Behavioral Sciences. Hillside, NJ: Lawrence Erlbaum.
Cook, T. et al. (2008). Impacts of School Improvement Status on Students with Disabilities. Technical Work Group Materials. Washington, DC: American Institutes for Research.
Davidian, M., A. Tsiatis, and S. Leon (2005). Semiparametric Estimation of Treatment Effect in a Pretest- Posttest Study with Missing Data. Statistical Science, 20(3), 261-301.
Decker, P., S. Glazerman, and D. Mayer (2004). The Effects of Teach For America on Students: Findings from a National Evaluation. Princeton, NJ: Mathematica Policy Research.
Donner, A. and N. Klar (2000). Design and Analysis of Cluster Randomization Trials in Health Research. London: Arnold.
Dynarski, M. and R. Agodini (2003). The Effectiveness of Educational Technology: Issues and Recommendations for the National Study. Princeton, NJ: Mathematica Policy Research.
Freedman, D. (2008). On Regression Adjustments to Experimental Data. Advances in Applied Mathematics, 40, 180-193.
Gleason, P. and R. Olsen (2004). Impact Evaluation of Charter School Strategies. Design Documents. Princeton, NJ: Mathematica Policy Research, Inc.
Heckman, J. and E. Vytlacil (2005). Structural Equations, Treatment Effects, and Econometric Policy Evaluation. Econometrica, 73(3), 669-738.
Hedges, L. (2004). Correcting Significance Tests for Clustering. Chicago, IL: University of Chicago Working Paper.
Hedges, L. and E. Hedberg (2007). Intraclass Correlation Values for Planning Group-Randomized Trials in Education. Educational Evaluation and Policy Analysis, 29(1), 60-87.
Hill, C., H. Bloom, A. Black, and M. Lipsey. Empirical Benchmarks for Interpreting Effect Sizes in Research. New York, NY: MDRC.
Holland, P (1986). Statistics and Causal Inference. Journal of the American Statistical Association, 81(396), 945-960.
Imbens, G. and D. Rubin (2007). Causal Inference: Statistical Methods for Estimating Causal Effects in Biomedical, Social, and Behavioral Sciences, Cambridge University Press.
Jackson, R. et al. (2007). National Evaluation of Early Reading First. Final Report to Congress. U.S. Department of Education, Institute of Education Sciences: Washington DC.
Kish, L. (1965). Survey Sampling. New York: John Wiley and Sons.
Liang, K. and S. Zeger (1986). Longitudinal Data Analysis Using Generalized Linear Models. Biometrika 73, 13-22.
Mayer, D., P. Peterson, D. Myers, C. Tuttle, and W. Howell. (2002). School Choice in New York City: An Evaluation of the School Choice Scholarships Program. Washington, DC: Mathematica Policy Research, Inc.
Murray, D. (1998). Design and Analysis of Group-Randomized Trials. Oxford: Oxford University Press.
Neyman, J. (1923). On the Application of Probability Theory to Agricultural Experiments: Essay on Principles. Chapter 9, Translated in Statistical Science, 1990: 5(4), 465-472.
Oakes, J and H. Feldman (2001). Statistical Power for Nonequivalent Pretest-Posttest Designs: The Impact of Change-Score Versus ANCOVA Models. Evaluation Review, 25(3), 3-28.
Puma, M. et al. (2005). Head Start Impact Findings: First Year Findings. Final Report to the U.S. Department of Health and Human Services, Administration for Children and Families: Washington DC.
Rao, C. (1973). Linear Statistical Inference and Its Applications. New York: Wiley and Sons.
Raudenbush, S. (1997). Statistical Analysis and Optimal Design for Cluster Randomized Trials. Psychological Methods, 2(2), 173-185.
Reichardt, C. (1979). Quasi-Experimentation: Design and Analysis for Field Settings. Boston: Houghton Mifflin.
Rubin, D. (1974). Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies. Journal of Education Psychology, 66, 688-701.
Rubin, D. (1977). Assignment to Treatment Group on the Basis of a Covariate. Journal of Education Statistics, 2(1), 1-26.
Schochet, P. (2007). Is Regression Adjustment Supported by the Neyman Model for Causal Inference?. Working Paper: Mathematica Policy Research, Inc.: Princeton NJ.
Schochet, P. (2008). Statistical Power for Random Assignment Evaluations of Education Programs. Journal of Educational and Behavioral Statistics, 33(1), 62-87.
Yang, L. and Tsiatis, A. (2001). Efficiency Study of Estimators for a Treatment Effects in a Pretest- Posttest Trial. American Statistician 55(4), 314-321.