Current state and prospects of R-packages for the design of experiments

TL;DR

This paper analyzes the current landscape of R-packages for experimental design, highlighting their usage, development patterns, and future prospects to improve experimental data quality.

Contribution

It provides an exploratory analysis of R-packages for experimental design, revealing development trends, package usage, and interface design considerations.

Findings

Few packages dominate experimental design in R

Development of packages occurs in isolated silos

Discussion on interface design and future prospects

Abstract

Re-running an experiment is generally costly and, in some cases, impossible due to limited resources; therefore, the design of an experiment plays a critical role in increasing the quality of experimental data. In this paper, we describe the current state of R-packages for the design of experiments through an exploratory data analysis of package downloads, package metadata, and a comparison of characteristics with other topics. We observed that experimental designs in practice appear to be sufficiently manufactured by a small number of packages, and the development of experimental designs often occurs in silos. We also discuss the interface designs of widely utilized R packages in the field of experimental design and discuss their future prospects for advancing the field in practice.