getCovMeanDiffs: Covariate Mean Differences In randChecks: Covariate Balance Checks: Randomization Tests and Graphical Diagnostics

Description

`getCovMeanDiffs` computes the covariate mean differences between a treatment and control group.

Usage

 `1` ```getCovMeanDiffs(X, indicator) ```

Arguments

 `X` A covariate matrix (rows correspond to subjects/units; columns correspond to covariates). `indicator` A vector of 1s and 0s (e.g., denoting treatment and control).

Value

The covariate mean differences between a treatment and control group, defined as treatment minus control.

Author(s)

Zach Branson

See also `lalondeMatches` for details about the Lalonde and matched datasets.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ``` #This loads the classic Lalonde (1986) dataset, #as well as two matched datasets: #one from 1:1 propensity score matching, #and one from cardinality matching, where #the standardized covariate mean differences are all below 0.1. data("lalondeMatches") #obtain the covariates for these datasets X.lalonde = subset(lalonde, select = -c(treat)) X.matched.ps = subset(lalonde.matched.ps, select = -c(treat,subclass)) X.matched.card = subset(lalonde.matched.card, select = -c(treat,subclass)) #the treatment indicators are indicator.lalonde = lalonde\$treat indicator.matched.ps = lalonde.matched.ps\$treat indicator.matched.card = lalonde.matched.card\$treat #the covariate mean differences are: getCovMeanDiffs(X = X.lalonde, indicator = indicator.lalonde) getCovMeanDiffs(X = X.matched.ps, indicator = indicator.matched.ps) getCovMeanDiffs(X = X.matched.card, indicator = indicator.matched.card) ```