The Multiplicative Mixed Model with the mumm R package as a General and Easy Random Interaction Model Tool

TL;DR

This paper introduces the mumm R package, providing a user-friendly and efficient tool for fitting multiplicative mixed models, which are useful across various scientific fields for modeling interactions between fixed and random effects.

Contribution

The paper presents the first open-source R package for multiplicative mixed models, facilitating their wider application and interpretation in scientific research.

Findings

Improved statistical inference using multiplicative mixed models.

Demonstrated application across sensometrics, agriculture, and medicine.

Showed advantages over traditional linear mixed models.

Abstract

Multiplicative mixed models can be applied in a wide range of scientific disciplines, since they are relevant in every situation where an interaction between a fixed effect and a random effect is present. Until now, no R package has been published, which can fit this type of models. The lack of user-friendly open source tools to fit these models, is the main reason that the models are not used as often as they could or should be. In this paper we introduce the user-friendly R package $\mathsf{mumm}$ for fitting multiplicative mixed models in a time-efficient manner. To illustrate the interpretation of the multiplicative term, we provide four data analysis examples, where the model is fitted to data sets that stem from studies in sensometrics, agriculture and medicine. With these examples it is shown that the statistical inference can be improved by using a multiplicative mixed model, instead of a linear mixed model which is usually employed.