Matching on Generalized Propensity Scores with Continuous Exposures
Check Weighted Covariate Balance Using Absolute Approach
A helper function for cgps_cw object
A helper function for cgps_erf object
A helper function for cgps_gps object
A helper function for cgps_pspop object
The 'CausalGPS' package.
Estimate Exposure Response Function
Check covariate balance using absolute approach
Computes distance on all possible combinations
Compute residual
Compute risk value
Create pseudo population using matching casual inference approach
Create pseudo population using weighting casual inference approach
Extend print function for cgps_pspop object
Set Logger Settings
Smooth exposure response function
Compute smoothed erf with kernsmooth approach
Compute smoothed erf with locpol approach
print summary of cgps_cw object
print summary of cgps_erf object
print summary of cgps_gps object
print summary of cgps_pspop object
Generate Prediction Model
Trim a data frame or an S3 object
Helper function
Check covariate balance
Check Kolmogorov-Smirnov (KS) statistics
Compile pseudo population
Find the closest data in subset to the original data
Compute counter or weight of data samples
Approximate density based on another vector
Compute minimum and maximum
Estimate generalized propensity score (GPS) values
Estimate hat (fitted) values
Estimate smoothed exposure-response function (ERF) for pseudo populati...
Estimate Parametric Exposure Response Function
Estimate semi-exposure-response function (semi-ERF).
Generate kernel function
Generate pseudo population
Generate synthetic data for the CausalGPS package
Get Logger Settings
Log system information
Match observations
Extend generic plot functions for cgps_cw class
Extend generic plot functions for cgps_cw class
Extend generic plot functions for cgps_gps class
Extend generic plot functions for cgps_pspop class
Extend print function for cgps_cw object
Extend print function for cgps_erf object
Extend print function for cgps_gps object
Provides a framework for estimating causal effects of a continuous exposure using observational data, and implementing matching and weighting on the generalized propensity score. Wu, X., Mealli, F., Kioumourtzoglou, M.A., Dominici, F. and Braun, D., 2022. Matching on generalized propensity scores with continuous exposures. Journal of the American Statistical Association, pp.1-29.
Useful links