# match_2C: Optimal Matching with Two Criteria. In match2C: Match One Sample using Two Criteria

 match_2C R Documentation

## Optimal Matching with Two Criteria.

### Description

This function performs an optimal statistical matching that sequentially balances the nominal levels (near-fine balance), the marginal distribution of the propensity score, and the total within-matched-pair Mahalanobis distance.

### Usage

match_2C(
Z,
X,
propensity,
dataset,
method = "maha",
exact = NULL,
caliper_left = 1,
caliper_right = 1,
k_left = NULL,
k_right = NULL,
fb_var = NULL,
controls = 1,
include = NULL
)

### Arguments

 Z A length-n vector of treatment indicator. X A n-by-p matrix of covariates with column names. propensity A vector of estimated propensity score (length(propensity) = length(Z)). dataset Dataset to be matched. method Method used to compute treated-control distance on the left. The default is the Mahalanobis distance. exact A vector of strings indicating which variables need to be exactly matched. caliper_left Size of caliper on the left network. caliper_right Size of caliper on the right network. k_left Connect each treated to k_left controls closest in the propensity score in the left network. k_right Connect each treated to k_right controls closest in the propensity score in the right network. fb_var A vector giving names of variables in matrix X to be finely balanced. controls Number of controls matched to each treated. Default is 1. include A binary vector indicating which controls must be included (length(include) = sum(1-Z)).

### Value

This function returns a list of three objects including the feasibility of the matching problem and the matched controls organized in different formats. See the documentation of the function construct_outcome or the vignette for more details.

### Examples

# We first prepare the input X, Z, propensity score

attach(dt_Rouse)
Z = IV
family=binomial)\$fitted.values
detach(dt_Rouse)

matching_output_double_calipers = match_2C(Z = Z, X = X,
propensity = propensity,
caliper_left = 0.05, caliper_right = 0.05,
k_left = 100, k_right = 100,
dataset = dt_Rouse)

# Please refer to the vignette for many more examples.

match2C documentation built on March 31, 2023, 6:39 p.m.