CBPS is an R package that implements the
covariate balancing propensity score proposed by
Imai and Ratkovic (2014;
JRSSB). The propensity score is estimated such that it
maximizes the resulting covariate balance as well as the prediction of
treatment assignment. The method, therefore, avoids an iteration
between model fitting and balance checking. The package also
implements several extensions of the CBPS beyond the cross-sectional,
binary treatment setting. The current version implements the CBPS for
longitudinal settings so that it can be used in conjunction with
marginal structural models (
Imai and Ratkovic, 2014;
JASA), treatments with three- and four-valued treatment
variables, continuous-valued treatments (
Fong, Hazlett, and Imai,
2015), and the situation with multiple distinct binary
treatments administered simultaneously. In the future it will be
extended to other settings including the generalization of
experimental and instrumental variable estimates.