balanceplot: Plot of Balance Statistics

Description

This function plots the balance statistics before and after matching.

Usage

balanceplot(matched, pscore.fit, 
    longcovnames = NULL, 
    main = "Standardized Difference in Means", 
    cex.main = 1, cex.vars = 0.8, cex.pts = 0.8, 
    mar = c(0, 5, 4, 2), mgp = c(2, 0.25, 0), 
    oma = c(0, 0, 0, 0), tcl = -0.2, ...)

Arguments

matched

matched data using matching function, see the example below.

pscore.fit

glm.fit object to get propensity scores.

longcovnames

long covariate names. If not provided, plot will use covariate variable name by default

main

title of the plot

cex.main

font size of main title

cex.vars

font size of variabel names

cex.pts

point size of the estimates

mar

margin of the plot, see ?par for details

mgp

axis margin of the plot, see ?par for details

oma

outer margin of the plot, see ?par for details

tcl

length of ticks, see ?par for details

...

other plot options may be passed to this function

Details

This function plots the balance statistics before and after matching. The open circle dots represent the unmatched balance statistics. The solid dots represent the matched balance statistics. The closer the value of the estimates to the zero, the better the treated and control groups are balanced after matching.

References

Andrew Gelman and Jennifer Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2006. (Chater 10)

Examples

Run this code

data(lalonde)
attach(lalonde)
fit <- glm(treat ~ re74 + re75 + age + factor(educ) + 
            black + hisp + married + nodegr + u74 + u75, 
            family=binomial(link="logit"))
pscores <- predict(fit, type="link")
matches <- matching(z=lalonde$treat, score=pscores)
matched <- lalonde[matches$matched,]  
balanceplot(matched, fit)