make_full_rank {WeightIt} | R Documentation |
Make a design matrix full rank
Description
When writing user-defined methods for use with
weightit()
, it may be necessary to take the potentially non-full rank
covs
data frame and make it full rank for use in a downstream
function. This function performs that operation.
Usage
make_full_rank(mat, with.intercept = TRUE)
Arguments
mat |
a numeric matrix or data frame to be transformed. Typically this
contains covariates. |
with.intercept |
whether an intercept (i.e., a vector of 1s) should be
added to |
Details
make_full_rank()
calls qr()
to find the rank and linearly
independent columns of mat
, which are retained while others are
dropped. If with.intercept
is set to TRUE
, an intercept column
is added to the matrix before calling qr()
. Note that dependent
columns that appear later in mat
will be dropped first.
See example at method_user
.
Value
An object of the same type as mat
containing only linearly
independent columns.
Note
Older versions would drop all columns that only had one value. With
with.intercept = FALSE
, if only one column has only one value, it
will not be removed, and it will function as though there was an intercept
present; if more than only column has only one value, only the first one
will remain.
See Also
Examples
set.seed(1000)
c1 <- rbinom(10, 1, .4)
c2 <- 1-c1
c3 <- rnorm(10)
c4 <- 10*c3
mat <- data.frame(c1, c2, c3, c4)
make_full_rank(mat) #leaves c2 and c4
make_full_rank(mat, with.intercept = FALSE) #leaves c1, c2, and c4