nawtilus - Navigated Weighting for the Inverse Probability Weighting
Implements the navigated weighting (NAWT) proposed by
Katsumata (2020) <arXiv:2005.10998>, which improves the inverse
probability weighting by utilizing estimating equations
suitable for a specific pre-specified parameter of interest
(e.g., the average treatment effects or the average treatment
effects on the treated) in propensity score estimation. It
includes the covariate balancing propensity score proposed by
Imai and Ratkovic (2014) <doi:10.1111/rssb.12027>, which uses
covariate balancing conditions in propensity score estimation.
The point estimate of the parameter of interest as well as
coefficients for propensity score estimation and their
uncertainty are produced using the M-estimation. The same
functions can be used to estimate average outcomes in missing
outcome cases.