Publications

Publications

Robins, J.M. (1998). Correction for non-compliance in equivalence trials. Statistics in Medicine, 17:269-302.

Robins, J.M. (1998). Structural nested failure time models. Survival Analysis, P.K. Andersen and N. Keiding, Section Editors. The Encyclopedia of Biostatistics, P. Armitage and T. Colton, Editors. Chichester, UK: John Wiley & Sons, pp. 4372-4389.

Robins, J.M. (1999). Association, causation, and marginal structural models. Synthese, 121:151-179.

Robins J.M. (1999). Marginal Structural Models versus Structural Nested Models as Tools for Causal Inference. Statistical Models in Epidemiology: The Environment and Clinical Trials. Halloran, M.E. and Berry, D., eds. NY: Springer-Verlag, pp. 95-134.

Robins, J.M. and Wasserman, L. (1999). On the impossibility of inferring causation from association without background knowledge. Computation, Causation, and Discovery. Eds. C. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, pp. 305-321.

Robins JM, Scharfstein D, Rotnitzky A. (1999). Sensitivity Analysis for Selection Bias and Unmeasured Confounding in Missing Data and Causal Inference Models. Statistical Models in Epidemiology: The Environment and Clinical Trials. Halloran, M.E. and Berry, D., eds. NY: Springer-Verlag, pp. 1-94

Robins, J.M. (1999). Testing and estimation of direct effects by reparameterizing directed acyclic graphs with structural nested models. Computation, Causation, and Discovery. Eds. C. Glymour and G. Cooper. Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, pp. 349-405.

Robins, J.M. and Wang, N. (2000). Inference for imputation estimators. Biometrika, 87:113-124.

Hernn, M., Brumback, B., and Robins, J.M. (2000). Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology.

Robins, J.M., Hernn, M. and Brumback, B. (2000). Marginal structural models and causal inference in epidemiology Epidemiology.

Robins, J.M. (2000). Robust estimation in sequentially ignorable missing data and causal inference models. Proceedings of the American Statistical Association.