If the Covariates matrix has an intercept, it will only be in the first column.
CovariatesThe numeric matrix that `model.matrix` would have returned.
OriginalVariableslook-up table associating Covariates columns with terms of the originating model formula
TermLabelslabels of terms of the originating model formula
contrastsContrasts, a list of contrasts or NULL, as returned by `model.matrix.default`
NotMissingMatrix of numbers in [0,1] with as many rows as the Covariates table but only one more col than there are distinct covariate missingness patterns (at least 1, nothing missing). First col is entirely T or 1, like an intercept.
NM.Covariatesinteger look-up table mapping Covariates columns to columns of NotMissing. (If nothing missing for that column, this is 0.)
NM.termsinteger look-up table mapping term labels to columns of NotMissing (0 means nothing missing in that column)
UnitWeightsvector of weights associated w/ rows of the ModelMatrixPlus
More on NotMissing slot: It's matrix of numbers in [0,1].
First col is entirely TRUE or 1, like an intercept, unless corresponding
UnitWeight is 0, in which case it may also be 0 (see below). Subsequent cols
present only if there are missing covariate values, in which case these cols are
named for terms (of the original calling formula or data frame) that possess
missing values. Terms with the same missing data pattern are mapped to a single
column of this matrix. If the ModelMatrixPlus is representing elements, each column should
be all 1s and 0s, indicating which elements have non-missing values for the term
represented by that column. If the ModelMatrixPlus as a whole represents clusters,
then there can be fractional values, but that situation should only arise in the
DesignOptions class exension of this class, so it's documented there.