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.

## Usage

maxCaliper(scores, z, widths, structure = NULL, exact = TRUE)

## Arguments

scores

A numeric vector of scores providing 1-D position of units

z

Treatment indicator vector

widths

A vector of caliper widths to try, will be sorted largest to smallest.

structure

Optional factor variable that groups the scores, as would be used by exactMatch. Including structure allows for wider calipers.

exact

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.

## Value

numeric The value of the largest caliper that creates a feasible problem. If no such caliper exists in widths, an error will be generated.