The tipr package.
D'Agostino McGowan, L. (2018). Improving Modern Techniques of Causal Inference: Finite Sample Performance of ATM and ATO Doubly Robust Estimators, Variance Estimation for ATO Estimators, and Contextualized Tipping Point Sensitivity Analyses for Unmeasured Confounding. PhD thesis, Vanderbilt University.
VanderWeele, TJ, and Peng D (2017). Sensitivity Analysis in Observational Research: Introducing the E-Value. Ann Intern Med, 167(4), 268–74.
Lin, DY, Psaty, BM, & Kronmal, RA. (1998). Assessing the sensitivity of regression results to unmeasured confounders in observational studies. Biometrics, 54(3), 948–963.
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