Robust Q-learning
Ertefaie A, McKay J. R., Oslin D., and Strawderman R. L. (2020). Journal of the American Statistical Association, DOI: 10.1080/01621459.2020.1753522 Q-learning is a regression-based approach that is
December 8, 2020
Archive
Constructing dynamic treatment regimes over indefinite time horizons
Ertefaie, A., and Strawderman, R. L. (2018). Biometrika, 105(4), 963-977. Existing methods for estimating optimal dynamic treatment regimes are limited to cases where a utility function is
December 1, 2020
Instrumental Variable Analysis with Censored Data in the Presence of Many Weak Instruments: Application to the Effect of Being Sentenced to Prison on Time to Employment
Ertefaie, A., Nguyen, A., Harding, D., Morenoff, J, and Yang, W. (2018). Annals of Applied Statistics, 12(4), 2647-2673. This article discusses an instrumental variable approach for analyzing
November 29, 2020
Quantitative Evaluation of the Trade-off of Strengthened Instruments and Sample Size in Observational Studies
Ertefaie, A., Small, D., and Rosenbaum, P. (2017). Journal of the American Statistical Association, 113(523), 1122-1134.
November 1, 2020
Outcome-adaptive lasso: Variable selection for causal inference
Shortreed, S., and Ertefaie, A. (2017), Biometrics, 73(4), 1111-1122. Methodological advancements, including propensity score methods, have resulted in improved unbiased estimation of treatment effects from observational data. Traditionally, a
October 1, 2020
