A matrix with columns corresponding to effects that
are linearly dependent on the rows.
The correlations of the estimable effects, with a zero
diagonal. An object of class "mtable" which has its own
Although the main method is for class "lm", alias is
most useful for experimental designs and so is used with fits from
Complete aliasing refers to effects in linear models that cannot be estimated
independently of the terms which occur earlier in the model and so
have their coefficients omitted from the fit. Partial aliasing refers
to effects that can be estimated less precisely because of
correlations induced by the design.
Some parts of the "lm" method require recommended package
MASS to be installed.
Chambers, J. M., Freeny, A and Heiberger, R. M. (1992)
Analysis of variance; designed experiments.
Chapter 5 of Statistical Models in S
eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.