plm (version 1.6-5)

model.frame.pFormula: model.frame and model.matrix for panel data

Description

Methods to create model frame and model matrix for panel data.

Usage

"model.frame"(formula, data, ..., lhs = NULL, rhs = NULL)

"model.matrix"(object, data, model = c("pooling","within","Between", "between","mean","random","fd"),  effect = c("individual","time","twoways"), rhs = 1, theta = NULL, ...) 
"model.matrix"(object, ...)

Arguments

object, formula

an object of class "pFormula" or an estimated model object of class "plm",

data

a pdata.frame, see Details,

effect

the effects introduced in the model, one of "individual", "time" or "twoways",

model

one of "pooling", "within", "between", "random", "fd" and "ht",

theta

the parameter for the transformation if model = "random",

lhs

inherited from package Formula (see there),

rhs

inherited from package Formula (see there),

...

further arguments.

Value

The model.frame methods return a pdata.frame. The model.matrix methods return a matrix.

Details

The lhs and rhs arguments are inherited from Formula, see there for more details. The model.frame methods return a pdata.frame object suitable as an input to plm's model.matrix. The model.matrix methods builds a model matrix with transformations performed as specified by the model and effect arguments (and theta if model = "random" is requested), in this case the supplied data argument should be a model frame created by plm's model.frame method. If not, it is tried to construct the model frame from the data. Constructing the model frame first ensures proper NA handling, see Examples.

See Also

pmodel.response for (transformed) response variable. pFormula, especially for coercing a formula to a pFormula. Formula from package Formula, especially for the lhs and rhs arguments.

Examples

# 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)

# then construct the (transformed) model matrix (design matrix)
# from formula and model frame
modmat <- model.matrix(pform, data = mf, model = "within")


## retrieve model frame and model matrix from an estimated plm object
fe_model <- plm(pform, data = pGrunfeld, model = "within")
model.frame(fe_model)
model.matrix(fe_model)

# same as constructed before
all.equal(mf, model.frame(fe_model), check.attributes = FALSE) # TRUE
all.equal(modmat, model.matrix(fe_model), check.attributes = FALSE) # TRUE