Estimation weighting models

Several built-in helper functions to generate estimation weights from a vector of unit totals, or an existing ei_spec() object.

Usage

ei_wgt_unif(x)

ei_wgt_prop(x)

ei_wgt_sqrt(x)

Arguments

x

A numeric vector of unit totals, or an existing ei_spec() object.

Value

A numeric vector of estimation weights with the same number of observations as x. These will have mean 1.

Functions

• ei_wgt_unif(): Uniform weights across units with any population. Appropriate if the unit-level variance is constant, i.e., homosekdastic.

• ei_wgt_prop(): Weights proportional to the totals. Appropriate if the unit-level variance is inversely proportional to the number of observations.

• ei_wgt_sqrt(): Weights proportional to the square root of the totals. Appropriate if the unit-level variance is inversely proportional to the square root of the number of observations.

Examples

data(elec_1968)

ei_wgt_unif(head(elec_1968$pres_total))
#> [1] 1 1 1 1 1 1

spec = ei_spec(head(elec_1968), predictors = vap_white:vap_other,
               outcome = pres_ind_wal, total = pres_total)
ei_wgt_prop(spec)
#> [1] 0.8851989 2.1516032 0.9151221 0.5219934 1.0283945 0.4976879
ei_wgt_sqrt(spec)
#> [1] 0.9722265 1.5157519 0.9885225 0.7465854 1.0479170 0.7289967