gnu: r-puniform: Move to (gnu packages cran).

* gnu/packages/statistics.scm (r-puniform): Move from here...
* gnu/packages/cran.scm (r-puniform): ...to here.

Change-Id: Ia826341194689fc3e35f8005d9f81de47b8746cf

1 files changed, 0 insertions, 65 deletions

diff --git a/gnu/packages/statistics.scm b/gnu/packages/statistics.scm
index 7075ac2fc1a..24201cbaf68 100644
--- a/gnu/packages/statistics.scm
+++ b/gnu/packages/statistics.scm
@@ -3182,71 +3182,6 @@ files into/from Pandas DataFrames.  It is a wrapper around the C library
 mediation and estimating power.")
     (license license:gpl2+)))
 
-(define-public r-puniform
-  (package
-    (name "r-puniform")
-    (version "0.2.7")
-    (source
-     (origin
-       (method url-fetch)
-       (uri (cran-uri "puniform" version))
-       (sha256
-        (base32
-         "15q5wlcps7387rjz7p1f5kifg1fl5yxxy7gjx6fvspvqwjkjbs4z"))))
-    (properties `((upstream-name . "puniform")))
-    (build-system r-build-system)
-    (propagated-inputs
-     (list r-adgoftest r-metafor r-numderiv r-rcpp r-rcpparmadillo))
-    (home-page
-     "https://github.com/RobbievanAert/puniform")
-    (synopsis
-     "Meta-Analysis Methods Correcting for Publication Bias")
-    (description
-     "This package provides meta-analysis methods that correct for publication
-bias and outcome reporting bias.  Four methods and a visual tool are currently
-included in the package.
-
-@enumerate
-@item The p-uniform method as described in van Assen, van Aert, and Wicherts
-(2015) @url{doi:10.1037/met0000025} can be used for estimating the average
-effect size, testing the null hypothesis of no effect, and testing for
-publication bias using only the statistically significant effect sizes of
-primary studies.
-
-@item The p-uniform* method as described in van Aert and van Assen (2019)
-@url{doi:10.31222/osf.io/zqjr9}.  This method is an extension of the p-uniform
-method that allows for estimation of the average effect size and the
-between-study variance in a meta-analysis, and uses both the statistically
-significant and nonsignificant effect sizes.
-
-@item The hybrid method as described in van Aert and van Assen (2017)
-@url{doi:10.3758/s13428-017-0967-6}.  The hybrid method is a meta-analysis
-method for combining an original study and replication and while taking into
-account statistical significance of the  original study.  The p-uniform and
-hybrid method are based on the statistical theory that the distribution of
-p-values is uniform conditional on the population effect size.
-
-@item
-The fourth method in the package is the Snapshot Bayesian Hybrid Meta-Analysis
-Method as described in van Aert and van Assen (2018)
-@url{doi:10.1371/journal.pone.0175302}.  This method computes posterior
-probabilities for four true effect sizes (no, small, medium, and large) based
-on an original study and replication while taking into account publication bias
-in the original study.  The method can also be used for computing the required
-sample size of the replication akin to power analysis in null hypothesis
-significance testing.
-@end enumerate
-
-The meta-plot is a visual tool for meta-analysis that
-provides information on the primary studies in the meta-analysis, the results
-of the meta-analysis, and characteristics of the research on the effect under
-study (van Assen and others, 2020).
-
-Helper functions to apply the Correcting for Outcome Reporting Bias (CORB)
-method to correct for outcome reporting bias in a meta-analysis (van Aert &
-Wicherts, 2020).")
-    (license license:gpl2+)))
-
 (define-public xlispstat
   (let ((commit "f1bea6053df658ee48612bf1f63c35de99e2c649")
         (revision "0"))