In jbryer/psa: Applied Propensity Score Analysis with R

Sensitivity Analysis {#chapter-sensitivity}

require(rbounds)
data(lalonde, package='Matching')

Y  <- lalonde$re78   #the outcome of interest
Tr <- lalonde$treat #the treatment of interest
attach(lalonde)
# The covariates we want to match on
X = cbind(age, educ, black, hisp, married, nodegr, u74, u75, re75, re74)
# The covariates we want to obtain balance on
BalanceMat <- cbind(age, educ, black, hisp, married, nodegr, u74, u75, re75, re74,
                    I(re74*re75))
detach(lalonde)

gen1 <- GenMatch(Tr=Tr, X=X, BalanceMat=BalanceMat, pop.size=50,
                  data.type.int=FALSE, print=0, replace=FALSE)
mgen1 <- Match(Y=Y, Tr=Tr, X=X, Weight.matrix=gen1, replace=FALSE)
summary(mgen1)

rbounds::psens(x = Y[mgen1$index.treated],
      y =Y[mgen1$index.contro],
      Gamma = 1.5, 
      GammaInc = .1)

rbounds::hlsens(x = Y[mgen1$index.treated],
       y = Y[mgen1$index.contro],
       Gamma = 1.5, 
       GammaInc = .1)

jbryer/psa documentation built on Nov. 17, 2023, 8:21 a.m.