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 prespecified 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 Mestimation. The same functions can be used to estimate average outcomes in missing outcome cases.
Package details 


Author  Hiroto Katsumata [aut, cre] 
Maintainer  Hiroto Katsumata <hrt.katsumata@gmail.com> 
License  GPL3 
Version  0.1.4 
Package repository  View on CRAN 
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