Uncertainty Intervals and Sensitivity Analysis for Missing Data

Implements functions to derive uncertainty intervals for (i) regression (linear and probit) parameters under missing not at random (non-ignorable missingness) as introduced in Genbäck, M., Stanghellini, E., and de Luna, X. (2015) and Genbäck, M., Ng, N., Stanghellini, E., and de Luna, X. (2018) . Also includes methods for doubly robust and outcome regression estimators of average causal effects under unobserved confounding as in Genbäck, M. and de Luna, X. (2018) , and for partial correlation analysis following Gorbach, T. and de Luna, X. (2018) .