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CBPS

Covariate Balancing Propensity Score

Implements the covariate balancing propensity score (CBPS) proposed by Imai and Ratkovic (2014) <DOI:10.1111/rssb.12027>. 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 optimal CBPS from Fan et al. (2016) <https://imai.fas.harvard.edu/research/CBPStheory.html>, several extensions of the CBPS beyond the cross-sectional, binary treatment setting. They include the CBPS for longitudinal settings so that it can be used in conjunction with marginal structural models from Imai and Ratkovic (2015) <DOI:10.1080/01621459.2014.956872>, treatments with three- and four-valued treatment variables, continuous-valued treatments from Fong, Hazlett, and Imai (2018) <DOI:10.1214/17-AOAS1101>, propensity score estimation with a large number of covariates from Ning, Peng, and Imai (2018) <arXiv:1812.08683>, 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.

Functions (23)

Blackwell

Blackwell Data for Covariate Balancing Propensity Score

CBIV

Covariate Balancing Propensity Score for Instrumental Variable Estimates (CBIV)

CBMSM

Covariate Balancing Propensity Score (CBPS) for Marginal Structural Models

CBMSM.fit

CBMSM.fit

CBPS

Covariate Balancing Propensity Score (CBPS) Estimation

CBPS.fit

CBPS.fit determines the proper routine (what kind of treatment) and calls the approporiate function. It also pre- and post-processes the data

LaLonde

LaLonde Data for Covariate Balancing Propensity Score

balance

Optimal Covariate Balance

balance.CBPS

Calculates the pre- and post-weighting difference in standardized means for covariate within each contrast

balance.CBPSContinuous

Calculates the pre- and post-weighting correlations between each covariate and the T

balance.npCBPS

Calls the appropriate balance function based on the number of treatments

hdCBPS

hdCBPS high dimensional CBPS method to parses the formula object and passes the result to hdCBPS.fit, which calculates ATE using CBPS method in a high dimensional setting.

npCBPS

Non-Parametric Covariate Balancing Propensity Score (npCBPS) Estimation

npCBPS.fit

npCBPS.fit

plot.CBMSM

Plotting CBPS Estimation for Marginal Structural Models

plot.CBPS

Plotting Covariate Balancing Propensity Score Estimation

plot.CBPSContinuous

Plot the pre-and-post weighting correlations between X and T

plot.npCBPS

Calls the appropriate plot function, based on the number of treatments