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.
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