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Abadie's kappa weights

Source: R/compliers.R
kappa_weights.Rd

Returns the per-observation Abadie kappa weight implied by a fitted drlate() object, $$\kappa = 1 - \frac{D(1 - Z)}{1 - p(X)} - \frac{(1 - D) Z}{p(X)},$$ where \(p(X)\) is the estimated instrument propensity score. The kappa weights identify the complier subpopulation: for any function \(g\) of the data, \(E[g \mid \mathrm{complier}] = E[\kappa g] / E[\kappa]\) (Abadie 2003). They are the weights used by complier_means() and are the Stata estat compliers, genkappa() object.

Usage

kappa_weights(object, normalize = TRUE)

Arguments

object

A fitted drlate() object (with keep_data = TRUE) using an instrument propensity score (any method except "ra").

normalize

Logical. If TRUE (default), the returned weights are the sampling-weighted, normalized weights \(w\kappa / \sum w\kappa\) that sum to one (the form used to compute complier averages). If FALSE, the raw kappa values are returned.

Value

A numeric vector with one entry per estimation-sample observation.

See also

complier_means()

Examples

fit <- drlate(lwage ~ age + educ, nvstat ~ age + educ,
              rsncode ~ age + educ, data = drlate_sim)
head(kappa_weights(fit))
#>             1             2             3             4             5 
#> -0.0008924724  0.0008266047 -0.0012620743  0.0008266047  0.0008266047 
#>             6 
#>  0.0008266047