data(RandHIE)female * child.num (family size).pioff (participation incentive payment).log(coins+1).idp=1,
ln(max(1,mdeoff/(0.01*coins))) otherwise.ghindx (general healt index)
with imputations of missing values.income (family income).num (family size).meddol (medical expenses).meddol > 0.Newhouse, J. P. (1999) RAND Health Insurance Experiment [in Metropolitan and Non-Metropolitan Areas of the United States], 1974--1982, ICPSR Inter-university Consortium for Political and Social Research, Aggregated Claims Series, Volume 1: Codebook for Fee-for-Service Annual Expenditures and Visit Counts, ICPSR 6439.
Wikipedia, RAND Health Insurance Experiment, http://en.wikipedia.org/wiki/RAND_Health_Insurance_Experiment.
## Cameron and Trivedi (2005): Section 16.6, page 553ff
data( RandHIE )
subsample <- RandHIE$year == 2 & !is.na( RandHIE$educdec )
selectEq <- binexp ~ logc + idp + lpi + fmde + physlm + disea +
hlthg + hlthf + hlthp + linc + lfam + educdec + xage + female +
child + fchild + black
outcomeEq <- lnmeddol ~ logc + idp + lpi + fmde + physlm + disea +
hlthg + hlthf + hlthp + linc + lfam + educdec + xage + female +
child + fchild + black
# ML estimation
cameron <- selection( selectEq, outcomeEq, data = RandHIE[ subsample, ] )
summary( cameron )
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