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authorLars-Dominik Braun <ldb@leibniz-psychology.org>2021-03-12 14:09:45 +0100
committerLars-Dominik Braun <ldb@leibniz-psychology.org>2021-03-12 14:34:18 +0100
commit23bfd152c286b7b6fd9ca6921ec9f78474e973db (patch)
tree632bbba284f0ff2ecec011fd485ad9679a6a3798 /gnu
parent8a51be3cddf2b829e4234a23aad347fb2381281a (diff)
gnu: Add r-ez.
* gnu/packages/cran.scm (r-ez): New variable.
Diffstat (limited to 'gnu')
-rw-r--r--gnu/packages/cran.scm40
1 files changed, 40 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index b65288390b..e6b205077b 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -27313,3 +27313,43 @@ package online.")
"This package provides a collection of templates to author
preregistration documents for scientific studies in PDF format.")
(license license:gpl3)))
+
+(define-public r-ez
+ (package
+ (name "r-ez")
+ (version "4.4-0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "ez" version))
+ (sha256
+ (base32
+ "0a58s94x576dfz7wcbivrr2hmdh5x1vy16zwkqp9fmdzqx38pagq"))))
+ (properties `((upstream-name . "ez")))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-car" ,r-car)
+ ("r-ggplot2" ,r-ggplot2)
+ ("r-lme4" ,r-lme4)
+ ("r-mass" ,r-mass)
+ ("r-matrix" ,r-matrix)
+ ("r-mgcv" ,r-mgcv)
+ ("r-plyr" ,r-plyr)
+ ("r-reshape2" ,r-reshape2)
+ ("r-scales" ,r-scales)
+ ("r-stringr" ,r-stringr)))
+ (home-page "https://github.com/mike-lawrence/ez")
+ (synopsis "Easy Analysis and Visualization of Factorial Experiments")
+ (description
+ "Facilitates easy analysis of factorial experiments, including purely
+within-Ss designs (a.k.a. \"repeated measures\"), purely between-Ss designs,
+and mixed within-and-between-Ss designs. The functions in this package aim to
+provide simple, intuitive and consistent specification of data analysis and
+visualization. Visualization functions also include design visualization for
+pre-analysis data auditing, and correlation matrix visualization. Finally,
+this package includes functions for non-parametric analysis, including
+permutation tests and bootstrap resampling. The bootstrap function obtains
+predictions either by cell means or by more advanced/powerful mixed effects
+models, yielding predictions and confidence intervals that may be easily
+visualized at any level of the experiment's design.")
+ (license license:gpl2+)))