makeFrontier: Compute the balance - sample size frontier.

In ChristopherLucas/MatchingFrontier: Computation of the Balance - Sample Size Frontier in Matching Methods for Causal Inference

Description

makeFrontier() computes the balance - frontier sample size and can be used with estimateEffects to estimate effects along the balance - sample size frontier.

Usage

makeFrontier(dataset, treatment, match.on, QOI = 'FSATT', metric =
             'Mahal', ratio = 'fixed', breaks = NULL, distance.mat =
             NULL)

Arguments

dataset	The data set contain containing the treatment, outcome, and variable to match on.
treatment	The name of the treatment.
match.on	A vector of colnames indicating which variables are to be matched on.
QOI	The quantity of interest to be estimated. By default, feasible sample average treatment effect on the treated or FSATT. The other option is SATT (sample average treatment effect on the treated).
metric	The metric used to measure imbalance. Defaults to average mahalanobis distance to nearest match. The other options are 'L1' and 'Euclid'.
ratio	Variable or fixed ratio. See King, Lucas, and Nielsen for details.
breaks	Can be used with L1 to provide user-specified breaks.
distance.mat	A treatment by control distance matrix.

References

King, Gary, Christopher Lucas, and Richard Nielsen. "The Balance-Sample Size Frontier in Matching Methods for Causal Inference." (2015).

Examples

data(lalonde)

match.on <- colnames(lalonde)[!(colnames(lalonde) %in% c('re78', 'treat'))]
my.frontier <- makeFrontier(dataset = lalonde,
                            treatment = 'treat',
                            match.on = match.on)

ChristopherLucas/MatchingFrontier documentation built on June 10, 2020, 6:01 p.m.