contr.isotonic.rev {logbin} | R Documentation |
Contrast Matrix for Reversed Isotonic Covariate
Description
Return something similar to a contrast matrix for a categorical covariate that we wish to be monotonically non-decreasing in a specified order.
Usage
contr.isotonic.rev(n, perm, contrasts = TRUE, sparse = FALSE)
Arguments
n |
a vector of levels for a factor, or the number of levels. |
perm |
a permutation of the levels of |
contrasts |
a logical indicating whether constrasts should be computed. |
sparse |
included for compatibility reasons. Has no effect. |
Details
This function is used in creating the design matrix for categorical covariates with a specified order under a particular parameterisation. This is required if a categorical covariate is defined as monotonic.
In the order specified by perm
, the coefficient
associated with each level is the sum of increments between
the following levels. That is, if there are a total of k
levels, the first level is defined as d_2 + d_3 + d_4 + \cdots + d_k
,
the second as d_3 + d_4 + \cdots + d_k
,
the third as d_4 + \cdots + d_k
, and so on. In fitting the model,
these increments are constrained to be non-positive.
Note that these are not ‘contrasts’ as defined in the
theory for linear models, rather this is used to define the
contrasts
attribute of each variable so that
model.matrix
produces the desired design
matrix.
Value
A matrix with n
rows and k
columns, with
k=n-1
if contrasts
is TRUE
and
k=n
if contrasts
is FALSE
.
Author(s)
Mark W. Donoghoe markdonoghoe@gmail.com
See Also
model.matrix
, which uses
contr.isotonic.rev
to create the design matrix.
contr.treatment
, contrasts
for
their usual use in regression models.
Examples
contr.isotonic.rev(4,1:4)
contr.isotonic.rev(4,c(1,3,2,4))
# Show how contr.isotonic.rev applies within model.matrix
x <- factor(round(runif(20,0,2)))
mf <- model.frame(~x)
contrasts(x) <- contr.isotonic.rev(levels(x), levels(x))
model.matrix(mf)