data(EU)
mvars <- c("socialist","rgdpc","FHc","FHp","trade")
dropvars <- c("countryname","population")
## In this example, I subset to the first 40 obs. to cut run-time
out <- case.match(data=EU[1:40,], id.var="countryname", leaveout.vars=dropvars,
distance="mahalanobis", case.N=2,
number.of.matches.to.return=10,
treatment.var="eu", max.variance=TRUE)
out$cases
if (FALSE) {
## All cases:
## Find the best matches of EU to non-EU countries
out <- case.match(data=EU, id.var="countryname", leaveout.vars=dropvars,
distance="mahalanobis", case.N=2,
number.of.matches.to.return=10,
treatment.var="eu", max.variance=TRUE)
out$cases
## Find the best matches while downweighting political variables
myvarweights <- c(1,1,.1,.1,.1)
names(myvarweights) <- c("rgdpc","trade","FHp","FHc","socialist")
myvarweights
(case.match(data=EU, id.var="countryname", leaveout.vars=dropvars,
distance="mahalanobis", case.N=2,
number.of.matches.to.return=10, treatment.var="eu",
max.variance=TRUE,varweights=myvarweights))$cases
## Find the best non-EU matches for Germany
tabGer <- case.match(data=EU, match.case="German Federal Republic",
id.var="countryname",leaveout.vars=dropvars,
distance="mahalanobis", case.N=2,
number.of.matches.to.return=10,max.variance=TRUE,
treatment.var="eu")
}
Run the code above in your browser using DataLab