- x
Any valid input to match_on. fullmatch will use
x and any optional arguments to generate a distance before performing
the matching.
If x is a numeric vector, there must also be passed a vector z
indicating grouping. Both vectors must be named.
Alternatively, a precomputed distance may be entered. A matrix of
non-negative discrepancies, each indicating the permissibility and
desirability of matching the unit corresponding to its row (a 'treatment') to
the unit corresponding to its column (a 'control'); or, better, a distance
specification as produced by match_on.
- min.controls
The minimum ratio of controls to treatments that is to
be permitted within a matched set: should be non-negative and finite. If
min.controls is not a whole number, the reciprocal of a whole number,
or zero, then it is rounded down to the nearest whole number or
reciprocal of a whole number.
When matching within subclasses (such as those created by
exactMatch), min.controls may be a named numeric vector
separately specifying the minimum permissible ratio of controls to treatments
for each subclass. The names of this vector should include names of all
subproblems distance.
- max.controls
The maximum ratio of controls to treatments that is
to be permitted within a matched set: should be positive and numeric.
If max.controls is not a whole number, the reciprocal of a
whole number, or Inf, then it is rounded up to the
nearest whole number or reciprocal of a whole number.
When matching within subclasses (such as those created by
exactMatch), max.controls may be a named numeric vector
separately specifying the maximum permissible ratio of controls to treatments
in each subclass.
- omit.fraction
Optionally, specify what fraction of controls or treated
subjects are to be rejected. If omit.fraction is a positive fraction
less than one, then fullmatch leaves up to that fraction of the control
reservoir unmatched. If omit.fraction is a negative number greater
than -1, then fullmatch leaves up to |omit.fraction| of the
treated group unmatched. Positive values are only accepted if
max.controls >= 1; negative values, only if min.controls <= 1.
If neither omit.fraction or mean.controls are specified, then
only those treated and control subjects without permissible matches among the
control and treated subjects, respectively, are omitted.
When matching within subclasses (such as those created by
exactMatch), omit.fraction specifies the fraction of
controls to be rejected in each subproblem, a parameter that can be made to
differ by subclass by setting omit.fraction equal to a named numeric
vector of fractions.
At most one of mean.controls and omit.fraction can be non-NULL.
- mean.controls
Optionally, specify the average number of controls per
treatment to be matched. Must be no less than than min.controls and no
greater than the either max.controls or the ratio of total number of
controls versus total number of treated. Some controls will likely not be
matched to ensure meeting this value. If neither omit.fraction or
mean.controls are specified, then only those treated and control
subjects without permissible matches among the control and treated subjects,
respectively, are omitted.
When matching within subclasses (such as those created by
exactMatch), mean.controls specifies the average number of
controls per treatment per subproblem, a parameter that can be made to
differ by subclass by setting mean.controls equal to a named numeric
vector.
At most one of mean.controls and omit.fraction can be non-NULL.
- tol
Because of internal rounding, fullmatch may
solve a slightly different matching problem than the one
specified, in which the match generated by
fullmatch may not coincide with an optimal solution of
the specified problem. tol times the number of subjects
to be matched specifies the extent to
which fullmatch's output is permitted to differ from an
optimal solution to the original problem, as measured by the
sum of discrepancies for all treatments and controls placed
into the same matched sets.
- data
Optional data.frame or vector to use to get order
of the final matching factor. If a data.frame, the rownames
are used. If a vector, the names are first tried, otherwise the contents
is considered to be a character vector of names. Useful to pass if you want to
combine a match (using, e.g., cbind) with the data that were used to
generate it (for example, in a propensity score matching).
- solver
Choose which solver to use. Currently implemented are RELAX-IV
and LEMON. Default of "", a blank string, will use RELAX-IV if the
rrelaxiv package is installed, otherwise will use LEMON.
To explicitly use RELAX-IV, pass string "RELAX-IV".
To use LEMON, pass string "LEMON". Optionally, to specify which algorithm
LEMON will use, pass the function LEMON with argument for the
algorithm name, "CycleCancelling", "CapacityScaling", "CostScaling", and
"NetworkSimplex". See this site for details on their differences:
https://lemon.cs.elte.hu/pub/doc/latest/a00606.html. CycleCancelling is
the default.
The CycleCancelling algorithm seems to produce results most closely
resembling those of optmatch versions prior to 1.0. We have observed the
other LEMON algorithms to produce different results when the
mean.controls is unspecified, or specified in such a way as to produce
an infeasible matching problem. When using a LEMON algorithm other than
CycleCancelling, we recommend setting the fullmatch_try_recovery
option to FALSE.
- ...
Additional arguments, passed to match_on (e.g. within)
or to specific methods.