The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

standardize: Tools for Standardizing Variables for Regression in R

Tools which allow regression variables to be placed on similar scales, offering computational benefits as well as easing interpretation of regression output.

Version: 0.2.2
Depends: R (≥ 3.6.0)
Imports: lme4, MASS, methods, stats, stringr
Suggests: afex, emmeans, knitr, lmerTest, rmarkdown, testthat
Published: 2021-03-05
DOI: 10.32614/CRAN.package.standardize
Author: Christopher D. Eager [aut, cre]
Maintainer: Christopher D. Eager <eager.stats at gmail.com>
BugReports: https://github.com/CDEager/standardize/issues
License: GPL (≥ 3)
URL: https://github.com/CDEager/standardize
NeedsCompilation: no
Citation: standardize citation info
Materials: README NEWS
CRAN checks: standardize results

Documentation:

Reference manual: standardize.pdf
Vignettes: Using the standardize package

Downloads:

Package source: standardize_0.2.2.tar.gz
Windows binaries: r-devel: standardize_0.2.2.zip, r-release: standardize_0.2.2.zip, r-oldrel: standardize_0.2.2.zip
macOS binaries: r-release (arm64): standardize_0.2.2.tgz, r-oldrel (arm64): standardize_0.2.2.tgz, r-release (x86_64): standardize_0.2.2.tgz, r-oldrel (x86_64): standardize_0.2.2.tgz
Old sources: standardize archive

Reverse dependencies:

Reverse imports: Countr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=standardize to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.