Performs simulation-based inference as an alternative to the delta method for obtaining valid confidence intervals and p-values for regression post-estimation quantities, such as average marginal effects and predictions at representative values. This framework for simulation-based inference is especially useful when the resulting quantity is not normally distributed and the delta method approximation fails. The methodology is described in Greifer, et al. (2025) tools:::Rd_expr_doi("10.32614/RJ-2024-015"). 'clarify' is meant to replace some of the functionality of the archived package 'Zelig'; see the vignette "Translating Zelig to clarify" for replicating this functionality.
Maintainer: Noah Greifer ngreifer@iq.harvard.edu (ORCID)
Authors:
Steven Worthington sworthington@iq.harvard.edu (ORCID)
Stefano Iacus siacus@iq.harvard.edu (ORCID)
Gary King king@harvard.edu (ORCID)
Greifer, N., Worthington, S., Iacus, S., & King, G. (2025). clarify: Simulation-Based Inference for Regression Models. The R Journal 16(2), 154–174. tools:::Rd_expr_doi("10.32614/RJ-2024-015")
Useful links: