2 files changed, 63 insertions(+), 65 deletions(-)

M gnu/packages/cran.scm
M gnu/packages/statistics.scm

@@ 5588,6 5588,69 @@ prototype-based, rather than class-based object oriented ideas.")
 understand the language at a deeper level.")
     (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 r-rcolorbrewer
   (package
     (name "r-rcolorbrewer")

@@ 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"))