Create Balance Table

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Description

Given an unmatched sample of treated and control units and (optionally) a matched sample from the same data, produces a table with pre- and post-match measures of covariate balance.

Usage

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balanceTable(df.orig, df.match = NULL, treatment, treat.wts = NULL, ctrl.wts = NULL,
mt.wts = NULL, mc.wts = NULL, verbose = FALSE)

Arguments

df.orig

a data frame containing the data before matching

df.match

an optional data frame containing the matched sample

treatment

name of the binary indicator for treatment status

treat.wts

optional weights for treated units in the original sample

ctrl.wts

optional weights for control units in the original sample

mt.wts

optional weights for treated units in the matched sample

mc.wts

optional weights for treated units in the matched sample

verbose

a logical value indicating whether detailed output should be printed.

Value

A matrix of balance measures, with one row for each covariate in df.orig except treatment, and columns for treated and control means, standardized differences in means, p-values from a 2-sample t-test, and p-values from either Fisher's exact test (if the covariate is binary) or a Wilcoxon signed rank test otherwise. If df.match is specified there are twice as many columns, one set for the pre-match samples and one set for the post-match samples.

Author(s)

Luke Keele, Penn State University, ljk20@psu.edu

Sam Pimentel, University of Pennsylvania, spi@wharton.upenn.edu

References

Rosenbaum, Paul R. (2002). Observational Studies. Springer-Verlag.

Rosenbaum, Paul R. (2010). Design of Observational Studies. Springer-Verlag.