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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tool_misc.R
\name{make.dummies}
\alias{make.dummies}
\alias{make.dummies.default}
\alias{make.dummies.data.frame}
\alias{make.dummies.pdata.frame}
\title{Create a Dummy Matrix}
\usage{
make.dummies(x, ...)
\method{make.dummies}{default}(x, base = 1L, base.add = TRUE, ...)
\method{make.dummies}{data.frame}(x, col, base = 1L, base.add = TRUE, ...)
\method{make.dummies}{pdata.frame}(x, col, base = 1L, base.add = TRUE, ...)
}
\arguments{
\item{x}{a factor from which the dummies are created (x is coerced to
factor if not yet a factor) for the default method or a data
data frame/pdata.frame for the respective method.}
\item{\dots}{further arguments.}
\item{base}{integer or character, specifies the reference level (base), if
integer it refers to position in \code{levels(x)}, if character the name
of a level,}
\item{base.add}{logical, if \code{TRUE} the reference level (base) is added
to the return value as first column, if \code{FALSE} the reference
level is not included.}
\item{col}{character (only for the data frame and pdata.frame methods), to
specify the column which is used to derive the dummies from,}
}
\value{
For the default method, a matrix containing the contrast-coded dummies,
dimensions are n x n where \code{n = length(levels(x))} if argument
\code{base.add = TRUE} or \code{n = length(levels(x)-1)} if \code{base.add = FALSE};
for the data frame and pdata.frame method, a data frame or pdata.frame,
respectively, with the dummies appropriately merged to the input as
last columns (column names are derived from the name of the column
used to create the dummies and its levels).
}
\description{
Contrast-coded dummy matrix created from a factor
}
\details{
This function creates a matrix of dummies from the levels of a factor.
In model estimations, it is usually preferable to not create the dummy matrix
prior to estimation but to simply specify a factor in the formula and let the
estimation function handle the creation of the dummies.
This function is merely a convenience wrapper around \code{stats::contr.treatment}
to ease the dummy matrix creation process shall the dummy matrix be explicitly
required. See Examples for a use case in LSDV (least squares dummy variable)
model estimation.
The default method uses a factor as main input (or something coercible to a
factor) to derive the dummy matrix from. Methods for data frame and pdata.frame
are available as well and have the additional argument \code{col} to specify the
the column from which the dummies are created; both methods merge the dummy
matrix to the data frame/pdata.frame yielding a ready-to-use data set.
See also Examples for use cases.
}
\examples{
library(plm)
data("Grunfeld", package = "plm")
Grunfeld <- Grunfeld[1:100, ] # reduce data set (down to 5 firms)
## default method
make.dummies(Grunfeld$firm) # gives 5 x 5 matrix (5 firms, base level incl.)
make.dummies(Grunfeld$firm, base = 2L, base.add = FALSE) # gives 5 x 4 matrix
## data frame method
Grun.dummies <- make.dummies(Grunfeld, col = "firm")
## pdata.frame method
pGrun <- pdata.frame(Grunfeld)
pGrun.dummies <- make.dummies(pGrun, col = "firm")
## Model estimation:
## estimate within model (individual/firm effects) and LSDV models (firm dummies)
# within model:
plm(inv ~ value + capital, data = pGrun, model = "within")
## LSDV with user-created dummies by make.dummies:
form_dummies <- paste0("firm", c(1:5), collapse = "+")
form_dummies <- formula(paste0("inv ~ value + capital + ", form_dummies))
plm(form_dummies, data = pGrun.dummies, model = "pooling") # last dummy is dropped
# LSDV via factor(year) -> let estimation function generate dummies:
plm(inv ~ value + capital + factor(firm), data = pGrun, model = "pooling")
}
\seealso{
\code{\link[stats:contrast]{stats::contr.treatment()}}, \code{\link[stats:contrasts]{stats::contrasts()}}
}
\author{
Kevin Tappe
}
\keyword{manip}
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