Additional Predictor with Maximum Effect Size

Tingting Zhan

2025-10-13

1 Introduction

The complete vignette of R package maxEff (v0.2.0)

https://rpubs.com/tingtingzhan/maxEff

documents the selection of one from many numeric predictors for a regression model, to ensure that the additional predictor has the maximum effect size.

The complete vignette exceeds the file size limit allowed on CRAN.

2 Prerequisite

2.1 Environment

Package maxEff (v0.2.0) requires R version 4.5.0 (released 2025-04-11) or higher (macOS, Windows, Linux).

An Integrated Development Environment (IDE), e.g., RStudio (Posit team 2025) or Positron, is not required, but highly recommended.

Environment on author’s computer 
Sys.info()[c('sysname', 'release', 'machine')]
#  sysname  release  machine 
# "Darwin" "25.1.0"  "arm64"
R.version
#                _                           
# platform       aarch64-apple-darwin20      
# arch           aarch64                     
# os             darwin20                    
# system         aarch64, darwin20           
# status                                     
# major          4                           
# minor          5.1                         
# year           2025                        
# month          06                          
# day            13                          
# svn rev        88306                       
# language       R                           
# version.string R version 4.5.1 (2025-06-13)
# nickname       Great Square Root

2.2 Dependency

The dependencies of package maxEff are detailed in the complete vignette.

Package maxEff requires the development versions of the spatstat.* family of packages (Baddeley, Rubak, and Turner 2015; Baddeley and Turner 2005). Installation instructions are provided in the complete vignette of package groupedHyperframe (Zhan and Chervoneva 2025, v0.3.0), Section 4.1.

2.3 Installation

Packages maxEff (v0.2.0) and groupedHyperframe (v0.3.0) can be installed using the following command.

utils::install.packages('groupedHyperframe')
utils::install.packages('maxEff')

2.4 Getting Started

Examples in the complete vignette require that the search path has

library(maxEff)
library(groupedHyperframe)
library(survival)

2.5 Acknowledgement

This work is supported by National Institutes of Health, U.S. Department of Health and Human Services grants

3 References

Baddeley, Adrian, Ege Rubak, and Rolf Turner. 2015. Spatial Point Patterns: Methodology and Applications with R. London: Chapman; Hall/CRC Press. https://www.routledge.com/Spatial-Point-Patterns-Methodology-and-Applications-with-R/Baddeley-Rubak-Turner/p/book/9781482210200/.
Baddeley, Adrian, and Rolf Turner. 2005. “spatstat: An R Package for Analyzing Spatial Point Patterns.” Journal of Statistical Software 12 (6): 1–42. https://doi.org/10.18637/jss.v012.i06.
Posit team. 2025. RStudio: Integrated Development Environment for r. Boston, MA: Posit Software, PBC. https://posit.co/.
Zhan, Tingting, and Inna Chervoneva. 2025. groupedHyperframe: Grouped Hyper Data Frame: An Extension of Hyper Data Frame. https://doi.org/10.32614/CRAN.package.groupedHyperframe.