Output Values
Regardless of the type of matching performed, the matchit
output object contains the following elements:11.2
- 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
149#149
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 2#2
that displays whether
the units were ineligible for matching due to common support
restrictions. It equals TRUE if unit 4#4
was discarded,
and it is set to FALSE otherwise.
- distance: a vector of length 2#2
with the estimated
distance measure for each unit.
- weights: a vector of length 2#2
with the weights
assigned to each unit in the matching process. Unmatched units have
weights equal to 0
. Matched treated units have weight 150#150
. 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.
Gary King
2011-11-29