The CAUSALTRT Procedure

References

  • Bang, H., and Robins, J. M. (2005). “Doubly Robust Estimation in Missing Data and Causal Inference Models.” Biometrics 61:962–973.

  • Berzuini, C., Dawid, P., and Bernardinelli, L., eds. (2012). Causality: Statistical Perspectives and Applications. Chichester, UK: John Wiley & Sons.

  • Cole, S. R., and Frangakis, C. E. (2009). “The Consistency Statement in Causal Inference: A Definition or an Assumption?” Epidemiology 20:3–5.

  • Hernán, M. A., and Robins, J. M. (2018). Causal Inference. Boca Raton, FL: Chapman & Hall/CRC. Forthcoming.

  • Imbens, G. W., and Rubin, D. B. (2015). Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. New York: Cambridge University Press.

  • Lunceford, J. K., and Davidian, M. (2004). “Stratification and Weighting via the Propensity Score in Estimation of Causal Treatment Effects: A Comparative Study.” Statistics in Medicine 23:2937–2960.

  • Morgan, S. L., and Winship, C. (2015). Counterfactuals and Causal Inference: Methods and Principles for Social Research. 2nd ed. New York: Cambridge University Press.

  • Murnane, R. J., and Willett, J. B. (2011). Methods Matter: Improving Causal Inference in Educational and Social Science Research. New York: Oxford University Press.

  • Neyman, J., Dabrowska, D. M., and Speed, T. P. (1990). “On the Application of Probability Theory to Agricultural Experiments: Essay on Principles, Section 9.” Statistical Science 5:465–472. Translated and edited by Dabrowska and Speed from the Polish original by Neyman (1923).

  • Pierce, D. A. (1982). “The Asymptotic Effect of Substituting Estimators for Parameters in Certain Types of Statistics.” Annals of Statistics 10:475–478.

  • Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1995). “Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data.” Journal of the American Statistical Association 90:106–121.

  • Rosenbaum, P. R., and Rubin, D. B. (1983). “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70:41–55.

  • Rubin, D. B. (1980). “Comment on D. Basu, 'Randomization Analysis of Experimental Data: The Fisher Randomization Test'.” Journal of the American Statistical Association 75:591–593.

  • Rubin, D. B. (1990). “Comment: Neyman (1923) and Causal Inference in Experiments and Observational Studies.” Statistical Science 5:472–480.

  • Rubin, D. B. (2005). “Causal Inference Using Potential Outcomes: Design, Modeling, Decisions.” Journal of the American Statistical Association 100:322–331.

  • Stefanski, L. A., and Boos, D. D. (2002). “The Calculus of M-Estimation.” American Statistician 56:29–38.

  • VanderWeele, T. J. (2009). “Concerning the Consistency Assumption in Causal Inference.” Epidemiology 20:880–883.

  • Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. 2nd ed. Cambridge, MA: MIT Press.

Last updated: December 09, 2022