Internal method. This version does not use the exact matching. Instead, this function should be called separately for each grouping.
trimatch.apply2(tpsa, caliper, nmatch, match.order, sd1, sd2, sd3)the results from trips
a vector of length one or three indicating the caliper to use for matching within each step. This is expressed in standardized units such that .25 means that matches must be within .25 of one standard deviation to be kept, otherwise the match is dropped.
number of closest matches to retain before moving to next edge. This can
be Inf in which case all matches within the caliper will be retained
through to the next step. For large datasets, evaluating all possible
matches within the caliper could be time consuming.
character vector of length three indicating the order in which the matching algorithm will processes. The default is to use start with the group the middle number of subjects, followed by the smallest, and then the largest.
standard deviation for propensity scores from model 1.
standard deviation for propensity scores from model 2.
standard deviation for propensity scores from model 3.