# contr.sdif

From MASS v7.3-19
by Brian Ripley

##### Successive Differences Contrast Coding

A coding for factors based on successive differences.

- Keywords
- models

##### Usage

`contr.sdif(n, contrasts = TRUE, sparse = FALSE)`

##### Arguments

- n
- The number of levels required.
- contrasts
- logical: Should there be
`n - 1`

columns orthogonal to the mean (the default) or`n`

columns spanning the space? - sparse
- logical. If true and the result would be sparse (only
true for
`contrasts = FALSE`

), return a sparse matrix.

##### Details

The contrast coefficients are chosen so that the coded coefficients in a one-way layout are the differences between the means of the second and first levels, the third and second levels, and so on. This makes most sense for ordered factors, but does not assume that the levels are equally spaced.

##### Value

- If
`contrasts`

is`TRUE`

, a matrix with`n`

rows and`n - 1`

columns, and the`n`

by`n`

identity matrix if`contrasts`

is`FALSE`

.

##### References

Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S.*
Fourth Edition, Springer.

##### See Also

##### Examples

```
contr.sdif(6)
zapsmall(ginv(contr.sdif(6)))
```

*Documentation reproduced from package MASS, version 7.3-19, License: GPL-2 | GPL-3*

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