Package index • vecmatch

Assessing initial imbalance

Visualize the covariate imbalances in the raw dataset before any propensity score estimation.

raincloud(): Examine the Imbalance of Continuous Covariates
mosaic(): Plot the Distribution of Categorical Covariates

Estimating generalized propensity scores

Estimate the treatment allocation probabilities and define the common support region.

estimate_gps(): Calculate Treatment Allocation Probabilities
csregion(): Filter the Data Based on Common Support Region

Matching

Match the observations across multiple treatment groups based on the estimated generalized propensity scores.

match_gps(): Match the Data Based on Generalized Propensity Scores

Evaluating matching quality

Assess the balance of the covariates and the descriptive statistics before and after matching.

balqual(): Evaluate Matching Quality

Optimizing the matching process

Search the parameter space of the estimation and matching functions and rerun the pipeline for the selected configurations.

optimize_gps(): Optimize the Matching Process via Random Search
make_opt_args(): Define the Optimization Parameter Space for Matching
select_opt(): Select Optimal Parameter Combinations from Optimization Results
get_select_params(): Extract Parameter Grid for Selected Configurations
run_selected_matching(): Rerun GPS Estimation and Matching for a Selected Configuration

Datasets

cancer: Patients with Colorectal Cancer and Adenoma

Package overview

vecmatch vecmatch-package: vecmatch: Vector Matching for Generalized Propensity Scores