dummy.coef {stats} | R Documentation |

## Extract Coefficients in Original Coding

### Description

This extracts coefficients in terms of the original levels of the
coefficients rather than the coded variables.

### Usage

dummy.coef(object, ...)
## S3 method for class 'lm':
dummy.coef(object, use.na = FALSE, ...)
## S3 method for class 'aovlist':
dummy.coef(object, use.na = FALSE, ...)

### 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. |

`...` |
arguments passed to or from other methods. |

### 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.

The method used has some limitations, and will give incomplete results
for terms such as `poly(x, 2))`

. However, it is adequate for
its main purpose, `aov`

models.

### Value

A list giving for each term the values of the coefficients. For a
multistratum `aov`

model, such a 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.

### See Also

`aov`

, `model.tables`

### Examples

options(contrasts=c("contr.helmert", "contr.poly"))
## From Venables and Ripley (2002) p.165.
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

*stats* version 2.2.1

Index]