| Title: | Likelihood-Based Evidence Ratios for Classical Statistical Tests |
|---|---|
| Description: | Implements likelihood-based evidence ratios for unified reporting in classical statistical testing. The package reports effect estimates, uncertainty intervals, and likelihood ratios on the log 10 scale derived from a single statistical model. It applies to standard normal mean tests, contingency tables, and regression coefficients, and provides a direct evidential measure while retaining classical error guarantees. For the Evidence Ratio Reporting Standard see Lawless (2026) <doi:10.5281/zenodo.18261076>. |
| Authors: | Dylan Lawless [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-8496-3725>) |
| Maintainer: | Dylan Lawless <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0 |
| Built: | 2026-05-21 06:01:10 UTC |
| Source: | https://github.com/cran/evidenceratio |
Computes an effect estimate, a Wald-style uncertainty interval, and a likelihood-based evidence ratio (log10 scale) from a single statistical model.
evidence_test(...)evidence_test(...)
... |
Arguments defining the data and model. |
An object of class evidence_result.
x <- sleep$extra[sleep$group == 1] evidence_test(x) tbl <- matrix(c(30, 70, 20, 80), nrow = 2) evidence_test(tbl) evidence_test(mpg ~ wt, data = mtcars, coef = "wt")x <- sleep$extra[sleep$group == 1] evidence_test(x) tbl <- matrix(c(30, 70, 20, 80), nrow = 2) evidence_test(tbl) evidence_test(mpg ~ wt, data = mtcars, coef = "wt")