Set and view the contrasts associated with a factor.

```
contrasts(x, contrasts = TRUE, sparse = FALSE)
contrasts(x, how.many) <- value
```

x

a factor or a logical variable.

contrasts

logical. See ‘Details’.

sparse

logical indicating if the result should be sparse
(of class `dgCMatrix`

), using
package Matrix.

how.many

How many contrasts should be made. Defaults to one
less than the number of levels of `x`

. This need not be the
same as the number of columns of `value`

.

value

either a numeric matrix (or a sparse or dense matrix of a
class extending `dMatrix`

from
package Matrix) whose columns give coefficients for
contrasts in the levels of `x`

, or the (quoted) name of a
function which computes such matrices.

If contrasts are not set for a factor the default functions from
`options("contrasts")`

are used.

A logical vector `x`

is converted into a two-level factor with
levels `c(FALSE, TRUE)`

(regardless of which levels occur in the
variable).

The argument `contrasts`

is ignored if `x`

has a matrix
`contrasts`

attribute set. Otherwise if `contrasts = TRUE`

it is passed to a contrasts function such as
`contr.treatment`

and if `contrasts = FALSE`

an identity matrix is returned. Suitable functions have a first
argument which is the character vector of levels, a named argument
`contrasts`

(always called with `contrasts = TRUE`

) and
optionally a logical argument `sparse`

.

If `value`

supplies more than `how.many`

contrasts, the
first `how.many`

are used. If too few are supplied, a suitable
contrast matrix is created by extending `value`

after ensuring
its columns are contrasts (orthogonal to the constant term) and not
collinear.

Chambers, J. M. and Hastie, T. J. (1992)
*Statistical models.*
Chapter 2 of *Statistical Models in S*
eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.

`C`

,
`contr.helmert`

,
`contr.poly`

,
`contr.sum`

,
`contr.treatment`

;
`glm`

,
`aov`

,
`lm`

.

# NOT RUN { utils::example(factor) fff <- ff[, drop = TRUE] # reduce to 5 levels. contrasts(fff) # treatment contrasts by default contrasts(C(fff, sum)) contrasts(fff, contrasts = FALSE) # the 5x5 identity matrix contrasts(fff) <- contr.sum(5); contrasts(fff) # set sum contrasts contrasts(fff, 2) <- contr.sum(5); contrasts(fff) # set 2 contrasts # supply 2 contrasts, compute 2 more to make full set of 4. contrasts(fff) <- contr.sum(5)[, 1:2]; contrasts(fff) # } # NOT RUN { ## using sparse contrasts: % useful, once model.matrix() works with these : ffs <- fff contrasts(ffs) <- contr.sum(5, sparse = TRUE)[, 1:2]; contrasts(ffs) stopifnot(all.equal(ffs, fff)) contrasts(ffs) <- contr.sum(5, sparse = TRUE); contrasts(ffs) # }