calculate_weights: Calculate regression weights

In regweight: Convenience Functions for Implicit Regression Weights

Calculate regression weights

Description

Given a model and a term of interest, calculate the Aronow and Samii (2015) doi: 10.1111/ajps.12185 regression weights and return an object which can be used to diagnose these implicit weights.

Usage

calculate_weights(mod, term)

Arguments

mod	The linear model object from lm or lm_robust.
term	String indicating the term for which to calculate the implicit regression weights. This must uniquely match a coefficient name (i.e. it must be a string which appears in only one element of coef(mod)).

Details

This calculates the implicit regression weights for a particular term in a given regression model.

In short, this calculates the weights for a coefficient β such that:

\frac{\mathrm{E}[w_i β_i]}{\mathrm{E}[w_i]} \to β

where β_i is the unit level effect. The expectation of w_i is the conditional variance of the variable of interest.

For details and examples, view the vignette: vignette("example-usage", package = "regweight")

Value

An object of class regweight containing:

term	The term in the regression for which weights were calculated.
model	The partial regression model object.
weights	The implicit regression weights.

References

Aronow, P.M. and Samii, C. (2016), "Does Regression Produce Representative Estimates of Causal Effects?". American Journal of Political Science, 60: 250-267. doi: 10.1111/ajps.12185

Examples

y <- rnorm(100)
a <- rbinom(100, 1, 0.5)
x <- rnorm(100)
m1 <- stats::lm(y ~ a + x)

w1 <- calculate_weights(m1, "a")

regweight documentation built on March 18, 2022, 7:53 p.m.