This function creates a ``list representation'' of a treatment-by-control distance matrix.
create_list_from_mat(
Z,
dist_mat,
p = NULL,
caliper = NULL,
k = NULL,
penalty = Inf
)This function returns a list that consists of three arguments: start_n, end_n, and d, as described above.
A length (n = n_t + n_c) vector of treatment indicators.
A treatment-by-control (n_t-by-n_c) distance matrix.
A vector of length (n_t + n_c) on which caliper applies (e.g. propensity scores)
Size of the caliper.
Connect each treated to the nearest k controls
Penalty for violating the caliper. Set to Inf by default.
This function creates a list representation of a treatment-by-control network. The list representation can be made sparse using a user-specified caliper. A list representation of a treatment-by-control distance matrix consists of the following arguments:
start_n: a vector containing the node numbers of the start nodes of each arc in the network.
end_n: a vector containing the node numbers of the end nodes of each arc in the network.
d: a vector containing the integer cost of each arc in the network.
Node 1,2,...,n_t are n_t treatment nodes; n_t + 1, n_t + 2, ..., n_t + n_c are n_c control nodes. start_n, end_n, and d should have the same lengths, all of which equal to the number of edges.
There are two options for users to make a network sparse. Option caliper is a value applied to the vector p to avoid connecting treated to controls whose covariate or propensity score defined by p is outside p +/- caliper. Second, within a specified caliper, sometimes there are still too many controls connected to each treated, and we can further trim down this number up to k by restricting our attention to the k nearest (in p) to each treated.
By default a hard caliper is applied, i.e., option penalty is set to Inf by default. Users may make the caliper a soft one by setting penalty to a large yet finite number.