Weighting for Covariate Balance in Observational Studies


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Documentation for package ‘WeightIt’ version 0.5.1

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boxplot.ps.cont Generalized Propensity Score Estimation using GBM
gbm.cont Generalized Propensity Score Estimation using GBM
make.full.rank Make a matrix full rank
method_cbps Covariate Balancing Propensity Score Weighting
method_ebal Entropy Balancing
method_ebcw Empirical Balancing Calibration Weighting
method_gbm Propensity Score Weighting Using Generalized Boosted Models
method_npcbps Nonparametric Covariate Balancing Propensity Score Weighting
method_optweight Optimization-Based Weighting
method_ps Propensity Score Weighting Using Generalized Linear Models
method_super Propensity Score Weighting Using SuperLearner
method_user User-Defined Functions for Estimating Weights
plot.ps.cont Generalized Propensity Score Estimation using GBM
print.summary.weightit Print and Summarize Output
print.summary.weightitMSM Print and Summarize Output
print.weightit Generate Balancing Weights
print.weightitMSM Generate Balancing Weights
ps.cont Generalized Propensity Score Estimation using GBM
summary.ps.cont Generalized Propensity Score Estimation using GBM
summary.weightit Print and Summarize Output
summary.weightitMSM Print and Summarize Output
trim Trim Large Weights
trim.numeric Trim Large Weights
trim.weightit Trim Large Weights
WeightIt Generate Balancing Weights
weightit Generate Balancing Weights
weightitMSM Generate Balancing Weights