blob: 6bffcde7f07dd72909188f050ab6422a15e0b9d4 [file] [log] [blame]
% File src/library/stats/man/dummy.coef.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2013 R Core Team
% Distributed under GPL 2 or later
\name{dummy.coef}
\title{Extract Coefficients in Original Coding}
\usage{
dummy.coef(object, \dots)
\method{dummy.coef}{lm}(object, use.na = FALSE, \dots)
\method{dummy.coef}{aovlist}(object, use.na = FALSE, \dots)
}
\alias{dummy.coef}
\alias{dummy.coef.lm}
\alias{dummy.coef.aovlist}
\arguments{
\item{object}{a linear model fit.}
\item{use.na}{logical flag for coefficients in a singular model. If
\code{use.na} is true, undetermined coefficients will be missing; if
false they will get one possible value.}
\item{\dots}{arguments passed to or from other methods.}
}
\description{
This extracts coefficients in terms of the original levels of the
coefficients rather than the coded variables.
}
\details{
A fitted linear model has coefficients for the contrasts of the factor
terms, usually one less in number than the number of levels. This
function re-expresses the coefficients in the original coding; as the
coefficients will have been fitted in the reduced basis, any implied
constraints (e.g., zero sum for \code{contr.helmert} or \code{contr.sum})
will be respected. There will be little point in using
\code{dummy.coef} for \code{contr.treatment} contrasts, as the missing
coefficients are by definition zero.
The method used has some limitations, and will give incomplete results
for terms such as \code{poly(x, 2)}. However, it is adequate for
its main purpose, \code{aov} models.
}
\value{
A list giving for each term the values of the coefficients. For a
multistratum \code{aov} model, such a list for each stratum.
}
\section{Warning}{
This function is intended for human inspection of the
output: it should not be used for calculations. Use coded variables
for all calculations.
The results differ from S for singular values, where S can be incorrect.
}
\seealso{\code{\link{aov}}, \code{\link{model.tables}}}
\examples{
options(contrasts = c("contr.helmert", "contr.poly"))
## From Venables and Ripley (2002) p.165.
npk.aov <- aov(yield ~ block + N*P*K, npk)
dummy.coef(npk.aov)
npk.aovE <- aov(yield ~ N*P*K + Error(block), npk)
dummy.coef(npk.aovE)
}
\keyword{models}