optmatch class describes the results of an optimal full matching
pairmatch). For the
most part, these objects can be treated as
The summary function quantifies
optmatch objects on the effective sample
size, the distribution of distances between matched units, and how well the
match reduces average differences.
1 2 3
An optional propensity model (the result of
a call to
Additional arguments to pass to
To minimize the the display of a groups with many treated and few controls, all groups with more than 5 treated units will be summarized as “5+”. This is the reciprocal of the default value (1/5 = 0.2). Lower this value to see more groups.
A points in the ECDF at which the distances between units will be displayed.
optmatch objects descend from
Elements of this vector correspond to members of the treatment and control
groups in reference to which the matching problem was posed, and are named
accordingly; the names are taken from the row and column names of
distance. Each element of the vector is either
unavailability of any suitable matches for that element, or the
concatenation of: (i) a character abbreviation of the name of the subclass
(as encoded using
exactMatch) (ii) the string
(iii) a non-negative integer. In this last place, positive whole numbers
indicate placement of the unit into a matched set and
that all or part of the matching problem given to
fullmatch was found
to be infeasible. The functions
matchfailed distinguish these
fullmatch returns various data about the matching
process and its result, stored as attributes of the named vector which is
its primary output. In particular, the
exceedances attribute gives
upper bounds, not necessarily sharp, for the amount by which the sum of
distances between matched units in the result of
the least possible sum of distances between matched units in a feasible
solution to the matching problem given to
fullmatch. (Such a bound
is also printed by
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