Stepwise regression is a statistical technique used for model selection. This package streamlines stepwise regression analysis by supporting multiple regression types, incorporating popular selection strategies, and offering essential metrics. It enables users to apply multiple selection strategies and metrics in a single function call, visualize variable selection processes, and export results in various formats. However, StepReg should not be used for statistical inference unless the variable selection process is explicitly accounted for, as it can compromise the validity of the results. This limitation does not apply when StepReg is used for prediction purposes. We validated StepReg's accuracy using public datasets within the SAS software environment. Additionally, StepReg features an interactive Shiny application to enhance usability and accessibility.
Package details |
|
---|---|
Author | Junhui Li [cre] (<https://orcid.org/0000-0003-3973-1700>), Junhui Li [aut], Kai Hu [aut], Xiaohuan Lu [aut], Kun Cheng [ctb], Sushmita N Nayak [ctb], Cesar Bautista Sotelo [ctb], Michael A Lodato [ctb], Wenxin Liu [aut], Lihua Julie Zhu [aut] |
Maintainer | Junhui Li <junhui.li11@umassmed.edu> |
License | MIT + file LICENSE |
Version | 1.5.8 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.