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Provides a robust implementation of information-theoretic moderation analysis using multi-model inference based on Akaike's Information Criterion (AIC) and its small-sample corrected form (Corrected AIC). The package enables researchers to compare competing model specifications and helps distinguish true interaction effects from nonlinear relationships that may produce spurious moderation. The methods build on Daryanto (2019) <doi:10.1016/j.jbusres.2019.06.012>.
| Version: | 0.1.29 |
| Imports: | stats, ggplot2, broom, lmtest, sandwich, rlang |
| Suggests: | knitr, rmarkdown |
| Published: | 2026-05-29 |
| DOI: | 10.32614/CRAN.package.ModLR |
| Author: | Ahmad Daryanto [aut, cre] |
| Maintainer: | Ahmad Daryanto <ahdar_2000 at yahoo.com> |
| License: | MIT + file LICENSE |
| URL: | https://github.com/ahdar1/ModLR |
| NeedsCompilation: | no |
| Citation: | ModLR citation info |
| Materials: | README |
| CRAN checks: | ModLR results |
| Reference manual: | ModLR.html , ModLR.pdf |
| Vignettes: |
Introduction to ModLR (source, R code) |
| Package source: | ModLR_0.1.29.tar.gz |
| Windows binaries: | r-devel: ModLR_0.1.29.zip, r-release: ModLR_0.1.29.zip, r-oldrel: ModLR_0.1.29.zip |
| macOS binaries: | r-release (arm64): ModLR_0.1.29.tgz, r-oldrel (arm64): ModLR_0.1.29.tgz, r-release (x86_64): ModLR_0.1.29.tgz, r-oldrel (x86_64): ModLR_0.1.29.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.