Navigated Weighting for the Inverse Probability Weighting

Implements the navigated weighting (NAWT) proposed by Katsumata (2020) , 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) , 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.


Reference manual

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0.1.4 by Hiroto Katsumata, a year ago

Browse source code at

Authors: Hiroto Katsumata [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports MASS

Suggests hypergeo, testthat

See at CRAN