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  Complete aliasing refers to effects in linear models that cannot be estimated
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  Complete aliasing refers to effects in linear models that cannot be estimated
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  independently of the terms which occur earlier in the model and so
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  independently of the terms which occur earlier in the model and so
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  have their coefficients omitted from the fit. Partial aliasing refers
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  have their coefficients omitted from the fit. Partial aliasing refers
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  to effects that can be estimated less precisely because of
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  to effects that can be estimated less precisely because of
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  correlations induced by the design.
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  correlations induced by the design.
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  Some parts of the \code{"lm"} method require recommended package
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  Some parts of the \code{"lm"} method require recommended package
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  \CRANpkg{MASS} to be installed.
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  \CRANpkg{MASS} to be installed.
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}
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}
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\value{
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\value{
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  A list (of \code{\link{class}} \code{"\link{listof}"}) containing components
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  A list (of \code{\link{class}} \code{"\link{listof}"}) containing components
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  \item{Model}{Description of the model; usually the formula.}
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  \item{Model}{Description of the model; usually the formula.}
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  \item{Complete}{A matrix with columns corresponding to effects that
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  \item{Complete}{A matrix with columns corresponding to effects that
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}
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}
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\author{
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\author{
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  The design was inspired by the S function of the same name described
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  The design was inspired by the S function of the same name described
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  in Chambers \emph{et al} (1992).
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  in Chambers \emph{et al} (1992).
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}
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}
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\examples{\donttest{
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\examples{\donttest{% as it loads  MASS
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op <- options(contrasts = c("contr.helmert", "contr.poly"))
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op <- options(contrasts = c("contr.helmert", "contr.poly"))
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npk.aov <- aov(yield ~ block + N*P*K, npk)
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npk.aov <- aov(yield ~ block + N*P*K, npk)
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alias(npk.aov)
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alias(npk.aov)
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options(op)  # reset
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options(op)  # reset
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}}
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}}