pmodel.response {plm} | R Documentation |
pmodel.response has several methods to conveniently extract the response of several objects.
pmodel.response(object, ...) ## S3 method for class 'data.frame' pmodel.response(object, ...) ## S3 method for class 'formula' pmodel.response(object, data, ...) ## S3 method for class 'plm' pmodel.response(object, ...)
object |
an object of class |
data |
a |
... |
further arguments. |
The model response is extracted from a pdata.frame
(where the response
must reside in the first column; this is the case for a model frame), a pFormula
+ data
or a
plm
object, and the transformation specified by effect
and model
is
applied to it.
Constructing the model frame first ensures proper NA handling and the response being
placed in the first column, see also Examples for usage.
A pseries except if model responses' of a "between"
or "fd" model as
these models "compress" the data (the number of observations used in estimation is smaller
than the original data due to the specific transformation). A numeric is returned for the
"between" and "fd" model.
Yves Croissant
plm
's model.matrix
for (transformed) model matrix and the
corresponding model.frame
method to construct a model frame.
# First, make a pdata.frame data(Grunfeld) pGrunfeld <- pdata.frame(Grunfeld) # then make a model frame from a pFormula and a pdata.frame pform <- pFormula(inv ~ value + capital) mf <- model.frame(pform, data = pGrunfeld) # construct (transformed) response of the within model resp <- pmodel.response(pform, data = mf, model = "within", effect = "individual") # retrieve (transformed) response directly from model frame resp_mf <- pmodel.response(mf, model = "within", effect = "individual") # retrieve (transformed) response from a plm object, i.e. an estimated model fe_model <- plm(pform, data = pGrunfeld, model = "within") pmodel.response(fe_model) # same as constructed before all.equal(resp, pmodel.response(fe_model), check.attributes = FALSE) # TRUE