exactMatch | R Documentation |
An exact match is one based on a factor. Within a level, all observations are allowed to be matched. An exact match can be combined with another distance matrix to create a set of matching subproblems.
exactMatch(x, ...)
## S4 method for signature 'vector'
exactMatch(x, treatment)
## S4 method for signature 'formula'
exactMatch(x, data = NULL, subset = NULL, na.action = NULL, ...)
x |
A factor vector or a formula, used to select method. |
... |
Additional arguments for methods. |
treatment |
A logical or binary vector the same length as |
data |
A |
subset |
an optional vector specifying a subset of observations to be used |
na.action |
A function which indicates what should happen when
the data contain |
exactMatch
creates a block diagonal matrix of 0s and
Inf
s. The pairs with 0 entries are within the same level of
the factor and legitimate matches. Inf
indicates units in
different levels. exactMatch
replaces the
structure.fmla
argument to several functions in previous
versions of optmatch. For the factor
method, the two
vectors x
and treatment
must be the same length. The
vector x
is interpreted as indicating the grouping factors
for the data, and the vector treatment
indicates whether a
unit is in the treatment or control groups. At least one of these
two vectors must have names. For the formula
method, the
data
argument may be omitted, in which case the method
attempts to find the variables in the environment from which the
function was called. This behavior, and the arguments subset
and na.action
, mimics the behavior of lm
.
A matrix like object, which is suitable to be given as
distance
argument to fullmatch
or
pairmatch
. The exact match will be only zeros and
Inf
values, indicating a possible match or no possible
match, respectively. It can be added to a another distance matrix
to create a subclassed matching problem.
Mark M. Fredrickson
caliper
, antiExactMatch
,
match_on
, fullmatch
,
pairmatch
data(nuclearplants)
### First generate a standard propensity score
ppty <- glm(pr~.-(pr+cost), family = binomial(), data = nuclearplants)
ppty.distances <- match_on(ppty)
### Only allow matches within the partial turn key plants
pt.em <- exactMatch(pr ~ pt, data = nuclearplants)
as.matrix(pt.em)
### Blunt matches:
match.pt.em <- fullmatch(pt.em)
print(match.pt.em, grouped = TRUE)
### Combine the propensity scores with the subclasses:
match.ppty.em <- fullmatch(ppty.distances + pt.em)
print(match.ppty.em, grouped = TRUE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.