In the contemporary era of big data, the volume of health data generated by healthcare providers, such as hospitals and dialysis facilities, has experienced a remarkable upsurge. As a result, traditional statistical tools for variable selection in high-dimensional data have encountered challenges in maintaining computational efficiency. In response to this issue, the grplasso R package has been meticulously developed, offering a powerful solution for efficient variable selection in multi-center data. Demonstrating its superiority, our statistical tool outperforms existing methods by a substantial margin, as validated through both simulated studies and real-world data.

Installation

Note: This package is still in its early stages of development, so please don’t hesitate to report any problems you may experience.

You can install ‘grplasso’ via github:

require("devtools")
require("remotes")
remotes::install_github("UM-KevinHe/grplasso", ref = "main")

We recommand to start with tutorial, as it provides an overview of the package’s usage, including model training, selection of penalization parameters, and post-estimation procedures.

Getting Help:

If you encounter any problems or bugs, please contact us at: ybshao@umich.edu, kevinhe@umich.edu.