cstar-package: Functions to examine the substantive robustness of...

In cstar: Substantive significance testing for regression estimates and marginal effects.

Description

Researchers care not only about the statistical significance of results, but also their substantive significance. This package implements a set of tools that allow researchers to use Bayesian decision-theoretic techniques set out in Esarey and Danneman (2014) to determine the substantive robustness of regression-based results. Specifically, given a set of regression results, a researcher can determine the minimum substantively meaningful relationship supported by his or her evidence under a variety levels of risk aversion.

Details

Package:	cstar
Type:	Package
Version:	1.0
Date:	2014-05-13
License:	GPL-2

Author(s)

Justin Esarey Maintainer: Justin Esarey <[e-mail]>

References

Esarey and Danneman (2014). A Quantitative Method for Substantive Robustness Assessment. Political Science Research and Methods.

cstar documentation built on May 1, 2019, 8:44 p.m.