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ModLR

Information-Theoretic Approach for Moderation Analysis

📦 Overview

ModLR implements an information-theoretic framework for moderation analysis using multi-model inference based on Akaike’s Information Criterion (AIC and AICc).

The package enables researchers to compare alternative moderation models and reduces the risk of identifying spurious moderation effects arising from nonlinear relationships.


đź“– Citation

If you use this package, please cite:

Daryanto, A. (2019). Avoiding spurious moderation effects: An information-theoretic approach to moderation analysis. Journal of Business Research, 103, 110–118.

This package provides an implementation of the information-theoretic framework proposed in this study.

✨ Key Features


📥 Installation

```r # Install from CRAN (after acceptance) install.packages(“ModLR”)

Load package

library(ModLR)

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.
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