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gnu: Add r-puniform.

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* gnu/packages/statistics.scm (r-puniform): New variable.
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Lars-Dominik Braun 2021-03-12 14:29:07 +01:00
parent 28df54d776
commit 8a8e8198ec
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@ -5990,3 +5990,71 @@ (define-public r-clubsandwich
@code{robu()} (from @code{robumeta}), and @code{rma.uni()} and @code{rma.mv()}
(from @code{metafor}).")
(license license:gpl3)))
(define-public r-puniform
(package
(name "r-puniform")
(version "0.2.4")
(source
(origin
(method url-fetch)
(uri (cran-uri "puniform" version))
(sha256
(base32
"0v2977y9cwjx74xk0ig745g09wn7nrcsrg4f6v315sglsm18iaa8"))))
(properties `((upstream-name . "puniform")))
(build-system r-build-system)
(propagated-inputs
`(("r-adgoftest" ,r-adgoftest)
("r-metafor" ,r-metafor)
("r-rcpp" ,r-rcpp)
("r-rcpparmadillo" ,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+)))