R packages by ruoqiyu

DiPs - Directional Penalties for Optimal Matching in Observational Studies

Improves the balance of optimal matching with near-fine balance by giving penalties on the unbalanced covariates with the unbalanced directions. Many directional penalties can also be viewed as Lagrange multipliers, pushing a matched sample in the direction of satisfying a linear constraint that would not be satisfied without penalization. Yu and Rosenbaum (2019) <doi:10.1111/biom.13098>.

Last updated 2 years ago

2.15 score 14 scripts 271 downloads

bigmatch - Making Optimal Matching Size-Scalable Using Optimal Calipers

Implements optimal matching with near-fine balance in large observational studies with the use of optimal calipers to get a sparse network. The caliper is optimal in the sense that it is as small as possible such that a matching exists. The main functions in the 'bigmatch' package are optcal() to find the optimal caliper, optconstant() to find the optimal number of nearest neighbors, and nfmatch() to find a near-fine balance match with a caliper and a restriction on the number of nearest neighbors. Yu, R., Silber, J. H., and Rosenbaum, P. R. (2020). <DOI:10.1214/19-sts699>.

Last updated 2 years ago

1.00 score 1 stars 9 scripts 286 downloads