Output Values

Regardless of the type of matching performed, the matchit output object contains the following elements:^4.2

• call: the original matchit() call.

• formula: the formula used to specify the model for estimating the distance measure.

• model: the output of the model used to estimate the distance measure. summary(m.out$model) will give the summary of the model where m.out is the output object from matchit().

• match.matrix: an $n_1 \times$ ratio matrix where:
  • the row names represent the names of the treatment units (which match the row names of the data frame specified in data).
  • each column stores the name(s) of the control unit(s) matched to the treatment unit of that row. For example, when the ratio input for nearest neighbor or optimal matching is specified as 3, the three columns of match.matrix represent the three control units matched to one treatment unit).
  • NA indicates that the treatment unit was not matched.

• discarded: a vector of length $n$ that displays whether the units were ineligible for matching due to common support restrictions. It equals TRUE if unit $i$ was discarded, and it is set to FALSE otherwise.

• distance: a vector of length $n$ with the estimated distance measure for each unit.

• weights: a vector of length $n$ with the weights assigned to each unit in the matching process. Unmatched units have weights equal to 0 . Matched treated units have weight $1$ . Each matched control unit has weight proportional to the number of treatment units to which it was matched, and the sum of the control weights is equal to the number of uniquely matched control units.

• subclass: the subclass index in an ordinal scale from 1 to the total number of subclasses as specified in subclass (or the total number of subclasses from full or exact matching). Unmatched units have NA.

• q.cut: the subclass cut-points that classify the distance measure.

• treat: the treatment indicator from data (the left-hand side of formula).

• X: the covariates used for estimating the distance measure (the right-hand side of formula). When applicable, X is augmented by covariates contained in mahvars and exact.

• nn: A basic summary table of matched data (e.g., the number of matched units)