Larger calipers permit more possible matches between treated and control
groups, which can be better for creating matches with larger effective sample
sizes. The downside is that wide calipers may make the matching problem too big
for processor or memory constraints. maxCaliper attempts to find a
caliper value, for a given vector of scores and a treatment indicator, that
will be possible given the maximum problem size constraints imposed by
fullmatch and pairmatch.
maxCaliper(scores, z, widths, structure = NULL, exact = TRUE)numeric The value of the largest caliper that creates a feasible
problem. If no such caliper exists in widths, an error will be
generated.
A numeric vector of scores providing 1-D position of units
Treatment indicator vector
A vector of caliper widths to try, will be sorted largest to smallest.
Optional factor variable that groups the scores, as would
be used by exactMatch. Including structure allows for wider
calipers.
A logical indicating if the exact problem size should be
computed (exact = TRUE) or if a more computationally efficient upper
bound should be used instead (exact = FALSE). The upper bound may lead
to narrower calipers, even if wider calipers would have sufficed using the
exact method.