Generalized Propensity Score Estimation and Matching for Multiple Groups
Evaluate Matching Quality
Filter the Data Based on Common Support Region
Calculate Treatment Allocation Probabilities
Extract Parameter Grid for Selected Configurations
Fixing bug in productplots::prodcalc
Define the Optimization Parameter Space for Matching
Match the Data Based on Generalized Propensity Scores
Plot the Distribution of Categorical Covariates
Optimize the Matching Process via Random Search
Examine the Imbalance of Continuous Covariates
Rerun GPS Estimation and Matching for a Selected Configuration
Select Optimal Parameter Combinations from Optimization Results
vecmatch: Vector Matching for Generalized Propensity Scores
Fixing bug in productplots::prodcalc
Implements the Vector Matching algorithm to match multiple treatment groups based on previously estimated generalized propensity scores. The package includes tools for visualizing initial confounder imbalances, estimating treatment assignment probabilities using various methods, defining the common support region, performing matching across multiple groups, and evaluating matching quality. For more details, see Lopez and Gutman (2017) <doi:10.1214/17-STS612>.