# matched: Identification of units placed into matched sets In markmfredrickson/optmatch: Functions for Optimal Matching

 matched R Documentation

## Identification of units placed into matched sets

### Description

Given a bipartite matching (object of class `optmatch`), create a logical vector of the same length indicating which units were and were not placed into matched sets.

### Usage

```matched(x)

unmatched()

matchfailed(x)
```

### Arguments

 `x` Vector of class `optmatch` (especially as generated by a call to `fullmatch`).

### Details

`matched` and `unmatched` indicate which elements of `x` do and do not belong to matched sets, as indicated by their character representations in `x`.

When `fullmatch` has been presented with an inconsistent combination of constraints and discrepancies between potential matches, so that there exists no matching (i) with finite total discrepancy within matched sets that (ii) respects the given constraints, then the matching problem is said to be infeasible. `TRUE`s in the output of `matchfailed` indicate that this has occurred.

### Value

A logical vector (without names).

### Note

To understand the output of `matchfailed` element-wise, note that `fullmatch` handles a matching problem in three steps. First, if `fullmatch` has been directed to match within subclasses, then it divides its matching problem into a subproblem for each subclass. Second, `fullmatch` removes from each subproblem those individual units that lack permissible potential matches (i.e. potential matches from which they are separated by a finite discrepancy). Such "isolated" units are flagged in such a way as to be indicated by `unmatched`, but not by `matchfailed`. Third, `fullmatch` presents each subproblem, with isolated elements removed, to an optimal matching routine. If such a reduced subproblem is found at this stage to be infeasible, then each unit contributing to it is so flagged as to be indicated by `matchfailed`.

### Author(s)

Ben Hansen

`fullmatch`

### Examples

```data(plantdist)

mxpl.fm0 <- fullmatch(plantdist) # A feasible matching problem
c(sum(matched(mxpl.fm0)), sum(unmatched(mxpl.fm0)))
sum(matchfailed(mxpl.fm0))
mxpl.fm1 <- fullmatch(plantdist, # An infeasible problem
max.controls=3, min.controls=3)
c(sum(matched(mxpl.fm1)), sum(unmatched(mxpl.fm1)))
sum(matchfailed(mxpl.fm1))

mxpl.si <- factor(c('a', 'a', 'c', rep('d',4), 'b', 'c', 'c', rep('d', 16)))
names(mxpl.si) <- LETTERS[1:26]
mxpl.exactmatch <- exactMatch(mxpl.si, c(rep(1, 7), rep(0, 26 - 7)))
# Subclass a contains two treated units but no controls;
# subclass b contains only a control unit;
# subclass c contains one treated and two control units;
# subclass d contains the remaining twenty units.
# only valid subproblems will be used

mcl <- c(1, Inf)

mxpl.fm2 <- fullmatch(plantdist + mxpl.exactmatch,
max.controls=mcl)
sum(matched(mxpl.fm2))

table(unmatched(mxpl.fm2), matchfailed(mxpl.fm2))

mxpl.fm2[matchfailed(mxpl.fm2)]

mxpl.fm2[unmatched(mxpl.fm2) &   # isolated units return as
!matchfailed(mxpl.fm2)] # unmatched but not matchfailed

```

markmfredrickson/optmatch documentation built on Aug. 5, 2022, 3:25 a.m.