effects {stats} | R Documentation |

## Effects from Fitted Model

### Description

Returns (orthogonal) effects from a fitted model, usually a linear
model. This is a generic function, but currently only has a methods for
objects inheriting from classes `"lm"`

and `"glm"`

.

### Usage

effects(object, ...)
## S3 method for class 'lm':
effects(object, set.sign = FALSE, ...)

### Arguments

`object` |
an **R** object; typically, the result of a model fitting function
such as `lm` . |

`set.sign` |
logical. If `TRUE` , the sign of the effects
corresponding to coefficients in the model will be set to agree with the
signs of the corresponding coefficients, otherwise the sign is
arbitrary. |

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

### Details

For a linear model fitted by `lm`

or `aov`

,
the effects are the uncorrelated single-degree-of-freedom values
obtained by projecting the data onto the successive orthogonal
subspaces generated by the QR decomposition during the fitting
process. The first *r* (the rank of the model) are associated with
coefficients and the remainder span the space of residuals (but are
not associated with particular residuals).

Empty models do not have effects.

### Value

A (named) numeric vector of the same length as
`residuals`

, or a matrix if there were multiple responses
in the fitted model, in either case of class `"coef"`

.

The first *r* rows are labelled by the corresponding coefficients,
and the remaining rows are unlabelled. Note that in rank-deficient
models the “corresponding” coefficients will be in a different
order if pivoting occurred.

### References

Chambers, J. M. and Hastie, T. J. (1992)
*Statistical Models in S.*
Wadsworth & Brooks/Cole.

### See Also

`coef`

### Examples

y <- c(1:3,7,5)
x <- c(1:3,6:7)
( ee <- effects(lm(y ~ x)) )
c(round(ee - effects(lm(y+10 ~ I(x-3.8))),3))# just the first is different

[Package

*stats* version 2.5.0

Index]