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author | Lars-Dominik Braun <ldb@leibniz-psychology.org> | 2021-03-12 14:29:07 +0100 |
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committer | Lars-Dominik Braun <ldb@leibniz-psychology.org> | 2021-03-12 14:34:22 +0100 |
commit | 8a8e8198ec4ebedd0400c8adcd85e15da3d43ca0 (patch) | |
tree | 4461e973ad41fc89fa5c3969422a2445098f4432 /gnu | |
parent | 28df54d77675a2247de17a8e45f57a0c613fb152 (diff) | |
download | guix-patches-8a8e8198ec4ebedd0400c8adcd85e15da3d43ca0.tar guix-patches-8a8e8198ec4ebedd0400c8adcd85e15da3d43ca0.tar.gz |
gnu: Add r-puniform.
* gnu/packages/statistics.scm (r-puniform): New variable.
Diffstat (limited to 'gnu')
-rw-r--r-- | gnu/packages/statistics.scm | 68 |
1 files changed, 68 insertions, 0 deletions
diff --git a/gnu/packages/statistics.scm b/gnu/packages/statistics.scm index 3f3c4e3912..9761b9ceaf 100644 --- a/gnu/packages/statistics.scm +++ b/gnu/packages/statistics.scm @@ -5990,3 +5990,71 @@ Methods are provided for a variety of fitted models, including @code{lm()} and @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+))) |