summary.sbchoice {DCchoice} | R Documentation |
sbchoice
estimation
Summary method for objects of class sbchoice
.
## S3 method for class 'sbchoice'
summary(object, ...)
## S3 method for class 'summary.sbchoice'
print(x, digits = max(3, getOption("digits") - 1), ...)
object |
an object of class |
x |
an object of class |
digits |
a number of digits to display. |
... |
optional arguments. Currently not in use. |
The function summary.sbchoice()
computes and returns a list of summary
statistics of the fitted model in object
of the "sbchoice"
class.
Some of the values are printed up to certain decimal places. Actual values of
individual components are displayed separately, for instance, by summary(object)$coefficients
.
See the Value section for a list of components.
Since the model for the single-bounded dichotomous choice CV data is estimated by glm
,
an object of class
"summary.sbchoice"
is constructed based on a "summary.glm"
class object. The summary of the "summary.glm"
class object is available by
summary(object)$glm.summary
. Other components computed by
summary.glm
are also accessible. See summary.glm
for details.
In addition to those available in the object
of the "sbchoice"
class,
the following list components are added.
glm.summary |
a summary of the |
glm.null.summary |
a summary of the |
loglik |
the value of the log-likelihood of the model. |
loglik.null |
the value of the log-likelihood of the null model. |
psdR2 |
McFadden's pseudo-R2 measure. |
adjpsdR2 |
McFadden's pseudo-R2 measure adjusted for the degrees of freedom. |
medianWTP |
the estimated median WTP. |
meanWTP |
the estimated mean WTP. |
trunc.meanWTP |
the estimated mean WTP truncated at the maximum bid. |
adj.trunc.meanWTP |
the truncated mean WTP with the adjustment of Boyle et~al.(1988). |
LR.test |
a vector containing the likelihood ratio test statistic, the degrees of freedom and the associated p-value. |
AIC |
information criterion (AIC and BIC). |
Boyle KJ, Welsh MP, Bishop RC (1988). “Validation of Empirical Measures of Welfare Change: Comment.” Land Economics, 64(1), 94–98.