Previous: Optimal Matching | Up: Examples | Next: Genetic Matching |

Full Matching

Full matching is a particular type of subclassification that forms the
subclasses in an optimal way (Rosenbaum, 2002; Hansen, 2004). A fully
matched sample is composed of matched sets, where each matched set
contains one treated unit and one or more controls (or one control
unit and one or more treated units). As with subclassification, the
only units not placed into a subclass will be those discarded (if a
`discard` option is specified) because they are outside the
range of common support. Full matching is optimal in terms of
minimizing a weighted average of the estimated distance measure
between each treated subject and each control subject within each
subclass.

Full matching can be performed with MATCHIT by setting
`method = "full"`. Just as with optimal matching, we use the
`optmatch` package (Hansen, 2004), which automatically loads
when needed. The following example with full matching (using the
default propensity score based on logistic regression) can also be run
by typing `demo(full)` at the R prompt:

> m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree + re74 + re75, data = lalonde, method = "full")

Gary King 2010-12-11