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dmphillippo
multinma:Bayesian Network Meta-Analysis of Individual and Aggregate Data
Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Maintained by David M. Phillippo. Last updated 3 days ago.
35 stars 9.34 score 163 scripts
smouksassi
ggquickeda:Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary Tables
Quickly and easily perform exploratory data analysis by uploading your data as a 'csv' file. Start generating insights using 'ggplot2' plots and 'table1' tables with descriptive stats, all using an easy-to-use point and click 'Shiny' interface.
Maintained by Samer Mouksassi. Last updated 13 days ago.
73 stars 8.34 score 27 scripts
insightsengineering
ggplot2.utils:Selected Utilities Extending 'ggplot2'
Selected utilities, in particular 'geoms' and 'stats' functions, extending the 'ggplot2' package. This package imports functions from 'EnvStats' <doi:10.1007/978-1-4614-8456-1> by Millard (2013), 'ggpp' <https://CRAN.R-project.org/package=ggpp> by Aphalo et al. (2023) and 'ggstats' <doi:10.5281/zenodo.10183964> by Larmarange (2023), and then exports them. This package also contains modified code from 'ggquickeda' <https://CRAN.R-project.org/package=ggquickeda> by Mouksassi et al. (2023) for Kaplan-Meier lines and ticks additions to plots. All functions are tested to make sure that they work reliably.
Maintained by Daniel Sabanés Bové. Last updated 9 months ago.
6 stars 6.26 score 14 scripts