JDS Journal of Data Science 1683-86021680-743X1680-743X School of Statistics, Renmin University of China JDS1192 10.6339/25-JDS1192 Computing in Data Science HIMA: An R Package for High-Dimensional Mediation Analysis ZhangHaixiang1† ZhengYinan2† HouLifang2 LiuLeilei.liu@wustl.edu3∗ School of Mathematics and KL-AAGDM, Tianjin University, Tianjin 300350, China Department of Preventive Medicine, Northwestern University, Chicago IL 60611, USA Division of Biostatistics, Washington University in St. Louis, St. Louis, MO 63110, USA Corresponding author. Email: lei.liu@wustl.edu.

Co-first authors.

 202597202500115 Supplementary Material

In the Supplementary Material, we provide the R code implementations corresponding to the illustrations presented in Section 4.

30820242362025 2025 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2025 Open access article under the CC BY license.

Mediation analysis plays an important role in many research fields, yet it is very challenging to perform estimation and hypothesis testing for high-dimensional mediation effects. We develop a user-friendly R package HIMA for high-dimensional mediation analysis with varying mediator and outcome specifications. The HIMA package is a comprehensive tool that accommodates various types of high-dimensional mediation models. This paper offers an overview of the functions within HIMA and demonstrates the practical utility of HIMA through simulated datasets. The HIMA package is publicly available from the Comprehensive R Archive Network at https://CRAN.R-project.org/package=HIMA.

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