NMAoutlier: Detecting Outliers in Network Meta-Analysis (original) (raw)

A set of functions providing several outlier (i.e., studies with extreme findings) and influential detection measures and methodologies in network meta-analysis : - simple outlier and influential detection measures - outlier and influential detection measures by considering study deletion (shift the mean) - plots for outlier and influential detection measures - Q-Q plot for network meta-analysis - Forward Search algorithm in network meta-analysis. - forward plots to monitor statistics in each step of the forward search algorithm - forward plots for summary estimates and their confidence intervals in each step of forward search algorithm.

Version: 0.1.18
Depends: R (≥ 3.0.0)
Imports: netmeta (≥ 0.9-7), meta (≥ 4.19-1), stats (≥ 3.4.3), parallel (≥ 3.4.1), MASS (≥ 7.3-47), reshape2 (≥ 1.4.3), ggplot2 (≥ 3.0.0), gridExtra (≥ 2.3)
Published: 2021-10-11
DOI: 10.32614/CRAN.package.NMAoutlier
Author: Maria Petropoulou ORCID iD [aut, cre], Guido Schwarzer ORCID iD [aut], Agapios Panos [aut], Dimitris Mavridis ORCID iD [aut]
Maintainer: Maria Petropoulou
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/petropouloumaria/NMAoutlier
NeedsCompilation: no
Materials: NEWS
In views: MetaAnalysis
CRAN checks: NMAoutlier results

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