Description Usage Arguments Details Value Author(s) References See Also Examples
control.overlap
returns a diagnostic plot showing the posterior mass over the number of control observations estimated in the common support region between the treatment and control groups.
1 2 3 | control.overlap(obj, color=TRUE, label.main="Assessing Control Overlap",
label.x="Size of Control Set", label.y="Mass")
|
obj |
A fitted SVMMatch object. |
color |
Whether to plot in color or black and white. TRUE or FALSE. |
label.main |
Main title for figure |
label.x |
X-axis label. |
label.y |
Y-axis label. |
Gives the posterior mass of control observations that fall in the common support region between treated and untreated obsevations. These are the only observations used in constructing the treatment effect.
counts |
Table containing posterior mass of number untreated observations. |
Marc Ratkovic
Ratkovic, Marc. 2014. "Balancing within the Margin: Causal Effect Estimation with Support Vector Machines." Working paper.
svmmatch
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## Not run:
##See svmmatch() for a full implementation
##Load data
data("LaLonde")
Data1<-LaLonde
Data1<-Data1[Data1$exper==0|Data1$treat==1,]
attach(Data1)
##Format X matrix
varnames<-c("age","educ","black","married","nodegr","hisp",
"re75","re74")
X<-cbind(Data1[,varnames],Data1$re75==0,Data1$re74==0)
X<-as.matrix(X)
##Fit model
set.seed(1)
m1.param<-svmmatch(treat, X, dv=re78, burnin=100, gibbs=100, thin=5)
##Assess ignorability:
#Assess control overlap--are there enough
#controls to balance the treated?
cont1<-control.overlap(m1.param)
## End(Not run)
|
Warning messages:
1: In par(par.old) : graphical parameter "cin" cannot be set
2: In par(par.old) : graphical parameter "cra" cannot be set
3: In par(par.old) : graphical parameter "csi" cannot be set
4: In par(par.old) : graphical parameter "cxy" cannot be set
5: In par(par.old) : graphical parameter "din" cannot be set
6: In par(par.old) : graphical parameter "page" cannot be set
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