krCI(obj, nsim = 1000, CI = 0.95, individual = NULL)
"print"(x, ...)
"dbchoice"
or "sbchoice"
."krCI"
.krCI()
returns an object of S3 class "krCI"
.
An object of "krCI"
is a list with the following components.-999
.-999
.The table contains the confidence intervals for the four types (mean, truncated mean,
truncated mean with adjustment and median) of WTP estimate from the ML estimation.
The adjustment for the truncated mean WTP is implemented by the method of Boyle
et~al.(1988).The generic function print()
is available for the object of class
"krCI"
and displays the table of simulated confidence intervals.nsim
times
from a multivariate normal distribution with a vector of the parameter estimates as a mean
and the variance-covariance matrix of the parameter estimates. Then, various WTPs are computed for
each draw of simulated parameters. As a result, we are able to build an empirical distribution
of the WTPs concerned, and hence the confidence intervals. For each WTP, and when nsim = 1000
,
the lower and the upper bound of the 95% confidence interval (CI = 0.95
) correspond to
the 26th and the 975th sorted estimates, respectively. Confidence intervals based on the bootstrap method are calculated by bootCI
.
Hole (2007) conducted simulation experiments to compare the performance of the method of Krinsky
and Robb (1986, 1990) with the bootstrap one.
A WTP of a specific individual (e.g., a representative respondent) can be estimated
when assigning covariates to individual
. See Example for details.
Hole AR (2007). A Comparison of Approaches to Estimating Confidence Intervals for Willingness to Pay Measure. Health Economics, 16, 827--840.
Krinsky I, Robb AL (1986). On Approximating the Statistical Properties of Elasticities. The Review of Economics and Statistics, 68, 715--719.
Krinsky I, Robb AL (1990). On Approximating the Statistical Properties of Elasticities: A Correction. The Review of Economics and Statistics, 72, 189--190.
bootCI
, dbchoice
, sbchoice
## See Examples in dbchoice and sbchoice.
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