Arguments for All Matching Methods

• formula: formula used to calculate the distance measure for matching (e.g., the propensity score model). It takes the usual syntax of R formulas, treat ~ x1 + x2, where treat is a binary treatment indicator, and x1 and x2 are the pre-treatment covariates. Both the treatment indicator and pre-treatment covariates must be contained in the same data frame, which is specified as data (see below). All of the usual R syntax for formulas work here. For example, x1:x2 represents the first order interaction term between x1 and x2, and I(x1 ^ 2) represents the square term of x1. See help(formula) for details.

• data: the data frame containing the variables called in formula.

• method: the matching method (default = "nearest", nearest neighbor matching). Currently, "exact" (exact matching), "full" (full matching), "nearest" (nearest neighbor matching), "optimal" (optimal matching), "subclass" (subclassification), "genetic" (genetic matching), and "cem" (coarsened exact matching) are available. Note that within each of these matching methods, MATCHIT offers a variety of options. See below for more details.

• verbose: a logical value indicating whether to print the status of the matching algorithm (default = FALSE).