pairwise_diff: Pairwise difference calculator

In gapclosing: Estimate Gaps Under an Intervention

Description

A function to estimate the pairwise differences of estimates made for each category.

Usage

pairwise_diff(category_means_data, category_name)

Arguments

category_means_data	Data frame containing two columns: the category-specific mean estimate (a column named estimate) and the category name (named as specified in category_name)
category_name	The name of the column containing the category identifier.

Value

A data frame with pairwise differences of estimate over pairs of categories.

References

Lundberg I (2021). "The gap-closing estimand: A causal approach to study interventions that close disparities across social categories." Sociological Methods and Research. Available at https://osf.io/gx4y3/.

Friedman J, Hastie T, Tibshirani R (2010). "Regularization Paths for Generalized Linear Models via Coordinate Descent." Journal of Statistical Software, 33(1), 1–22. https://www.jstatsoft.org/htaccess.php?volume=33&type=i&issue=01.

Wood S (2017). Generalized Additive Models: An Introduction with R, 2 edition. Chapman and Hall/CRC.

Wright MN, Ziegler A (2017). "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R." Journal of Statistical Software, 77(1), 1–17. doi: 10.18637/jss.v077.i01.

Examples

sim_data <- data.frame(example_category = c("A","B","C"),
                       estimate = c(1,2,3))
pairwise_diff(sim_data, category_name = "example_category")

gapclosing documentation built on Oct. 11, 2021, 9:07 a.m.