margEff
method computes the marginal effects of the explanatory variables
on the expected value of the dependent variable evaluated.
Please note that this functionality is currently not available
for panel data models.
"margEff"( object, xValues = NULL, calcVCov = TRUE, returnJacobian = FALSE, ... )
"summary"( object, ... )
object
of the margEff
method
must be an object of class "censReg"
(returned by censReg
);
argument object
of the summary
method
must be an object of class "margEff.censReg"
(returned by margEff.censReg
).NULL
(or not specified),
argument xValues
is set to the mean values
of the explanatory variables.TRUE
,
the approximate variance covariance matrices of the marginal effects
is calculated and returned as an attribute (see below).TRUE
,
the Jacobian of the marginal effects with respect to the coefficients
is returned as an attribute (see below).margEff.censReg
returns an object of class "margEff.censReg"
,
which is a vector of the marginal effects of the explanatory variables
on the expected value of the dependent variable evaluated
at the mean values of the explanatory variables.
The returned object has an attribute df.residual
,
which is equal to the degrees of freedom of the residuals.If argument calcVCov
is TRUE
,
the object returned by margEff.censReg
has an attribute vcov
,
which is a the approximate variance covariance matrices
of the marginal effects calculated
with the Delta method.If argument returnJacobian
is TRUE
,
the object returned by margEff.censReg
has an attribute jacobian
,
which is the Jacobian of the marginal effects
with respect to the coefficients.summary.margEff.censReg
returns
an object of class "summary.margEff.censReg"
,
which is a matrix with four columns,
where the first column contains the marginal effects,
the second column contains the standard errors of the marginal effects,
the third column contains the corresponding t-values,
and the fourth columns contains the corresponding P values.
censReg
, coef.censReg
,
and summary.censReg
## Kleiber & Zeileis ( 2008 ), page 142
data( "Affairs", package = "AER" )
estResult <- censReg( affairs ~ age + yearsmarried + religiousness +
occupation + rating, data = Affairs )
margEff( estResult )
summary( margEff( estResult ) )
margEff( estResult, xValues = c( 1, 40, 4, 2, 4, 4 ) )
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