Apply weighting function to a DesignOptions by stratum, returning results in a format suitable to be associated with an existing design and used in further calcs.
DesignWeights(design, stratum.weights = harmonic_times_mean_weight)data frame w/ rows for strata, cols sweights and wtratio.
DesignOptions
Stratum weights function. Will be fed a count data.frame with Tx.grp (indicating the treatment group), stratum.code, all other covariates and unit.weights.
The function expects its DesignOptions argument to represent aggregated data,
i.e. clusters not elements within clusters. Its stratum.weights argument
is a function that is applied to a data frame representing clusters,
with variables Tx.grp, stratum.code, covariates as named in the
design argument (a DesignOptions object), and unit.weights (either as
culled or inferred from originating balanceTest call or as aggregated up
from those unit weights). Returns a
weighting factor to be associated with each stratum, this factor determining the stratum
weight by being multiplied by mean of unit weights over clusters in that stratum.
Specifically, the function's value is a data frame of two variables,
sweights and wtratio, with rows representing strata.
The sweights vector represents internally
calculated or user-provided stratum.weights, one for each
stratum, scaled so that their sum is 1; in Hansen & Bowers (2008), these
weights are denoted \(w_{b}\). wtratio is the ratio of
sweights to the product of half the harmonic
mean of n_tb and n_cb, the number of treatment and control
clusters in stratum b, with the mean of the weights associated with
each of these clusters. In the notation of Hansen & Bowers
(2008), this is \(w_{b}/(h_b \bar{m}_b)\). Despite the name
‘wtratio’, this ratio's denominator is not a weight
in the sense of summing to 1 across strata. The ratio is expected
downstream in HB08 (in internal calculations
involving ‘wtr’).