Extract Coefficients in Original Coding

Usage

dummy.coef(object, ...)
dummy.coef.lm(object, use.na = FALSE)
dummy.coef.aovlist(object, use.na = FALSE)

print.dummy.coef[.list](x, ..., title)

Arguments

object a linear model fit
use.na logical flag for coefficients in a singular model. If use.na is true, undetermined coefficients will be missing; if false they will get one possible value.

Description

These extract 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 contr.helmert or contr.sum will be respected. There will be little point in using dummy.coef for contr.treatment contrasts, as the missing coefficients are by definition zero.

Value

A class "dummy.coef" list giving for each term the values of the coefficients. For a multistratum aov model, such a list (class "dummy.coef.list") for each stratum.

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.

Author(s)

B.D. Ripley

See Also

aov, model.tables

Examples

options(contrasts=c("contr.helmert", "contr.poly"))
## From Venables and Ripley (1997) p.210.
N <- c(0,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,1,0,1,0,1,1,0,0)
P <- c(1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,0,1,1,0)
K <- c(1,0,0,1,0,1,1,0,0,1,0,1,0,1,1,0,0,0,1,1,1,0,1,0)
yield <- c(49.5,62.8,46.8,57.0,59.8,58.5,55.5,56.0,62.8,55.8,69.5,
55.0, 62.0,48.8,45.5,44.2,52.0,51.5,49.8,48.8,57.2,59.0,53.2,56.0)

npk <- data.frame(block=gl(6,4), N=factor(N), P=factor(P),
                  K=factor(K), yield=yield)
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)

[Package Contents]