# calculate_weights: Calculate regression weights In regweight: Convenience Functions for Implicit Regression Weights

 calculate_weights R Documentation

## 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.