A class for representing covariate matrices after alignment within stratum, for a (single) given stratifying factor. There can also be a clustering variable, assumed to be nested within the stratifying variable.
CovariatesNumeric matrix, as in ModelMatrixPlus, except: will include NM columns; all columns presumed to have been stratum-centered (aligned)
UnitWeightsvector of weights associated w/ rows of Covariates
ZLogical indicating treatment assignment
StrataMatrixA sparse matrix with n rows and s columns, with 1 if the unit is in that stratification
StrataWeightRatioFor each unit, ratio of stratum weight to h_b; but see Details.
ClusterFactor indicating who's in the same cluster with who
OriginalVariablesLook up table associating Covariates cols to terms in the calling formula, as in ModelMatrixPlus
In contrast to DesignOptions, this class represents the combination of a single Covariates table, realized treatment assignment and treatment assignment scheme, not multiple treatment assignment schemes (designs). These Covariates are assumed to reflect regularization, s.t. missings have been patched with a value and then all of the covariate values have been aligned within each stratum. In lieu of a NotMissing slot there will be Covariates columns, also centered within a stratum, recording non-missingness of the original data.
Ordinarily the StrataWeightRatio slot has an entry for each unit, representing ratio of specified stratum weight to the product of h_b (the harmonic mean of n_tb and n_cb, the counts of treatment and control clusters in stratum b) with bar-w_b, (the arithmetic mean of aggregated cluster weights within that stratum). It can also be the numeric vector 1, without names, meaning the intended weight ratio is always 1.