doi:10.1093/bioinformatics/btz590>. SPRE statistics are precision weighted residuals that indicate the direction and extent with which individual study-effects in a meta-analysis deviate from the average genetic effect. Overly influential positive outliers have the potential to inflate average genetic effects in a meta-analysis whilst negative outliers might lower or change the direction of effect. See the 'getspres' website for documentation and examples <https://magosil86.github.io/getspres/>.">

getspres: SPRE Statistics for Exploring Heterogeneity in Meta-Analysis (original) (raw)

An implementation of SPRE (standardised predicted random-effects) statistics in R to explore heterogeneity in genetic association meta- analyses, as described by Magosi et al. (2019) <doi:10.1093/bioinformatics/btz590>. SPRE statistics are precision weighted residuals that indicate the direction and extent with which individual study-effects in a meta-analysis deviate from the average genetic effect. Overly influential positive outliers have the potential to inflate average genetic effects in a meta-analysis whilst negative outliers might lower or change the direction of effect. See the 'getspres' website for documentation and examples <https://magosil86.github.io/getspres/>.

Version: 0.2.0
Depends: R (≥ 3.1.0)
Imports: metafor (≥ 1.9-6), dplyr (≥ 0.4.1), plotrix (≥ 3.5-12), colorspace (≥ 1.2-6), RColorBrewer (≥ 1.1-2), colorRamps (≥ 2.3)
Suggests: knitr (≥ 1.10.5), testthat, covr, rmarkdown
Published: 2021-05-09
DOI: 10.32614/CRAN.package.getspres
Author: Lerato E Magosi [aut], Jemma C Hopewell [aut], Martin Farrall [aut], Lerato E Magosi [cre]
Maintainer: Lerato E Magosi
BugReports: https://github.com/magosil86/getspres/issues
License: MIT + file
URL: https://magosil86.github.io/getspres/
NeedsCompilation: no
Citation: getspres citation info
Materials: NEWS
In views: MetaAnalysis
CRAN checks: getspres results

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