baymedr: Computation of Bayes Factors for Common Biomedical Designs

BAYesian inference for MEDical designs in R. Convenience functions for the computation of Bayes factors for common biomedical research designs. Implemented are functions to test the equivalence (equiv_bf), non-inferiority (infer_bf), and superiority (super_bf) of an experimental group compared to a control group. Bayes factors for these three tests can be computed based on raw data (x, y) or summary statistics (n_x, n_y, mean_x, mean_y, sd_x, sd_y [or ci_margin and ci_level]), making it possible to reanalyse findings (e.g., from publications) without the need to obtain the raw data.

Version: 0.1.0
Depends: R (≥ 3.2.0)
Imports: methods, rlang, stats, stringr
Suggests: knitr, rmarkdown, testthat
Published: 2019-10-21
Author: Maximilian Linde ORCID iD [aut, cre], Don van Ravenzwaaij ORCID iD [aut], Quentin F. Gronau ORCID iD [ctb]
Maintainer: Maximilian Linde <maximilian.linde.92 at gmail.com>
BugReports: https://github.com/maxlinde/baymedr/issues
License: GPL-3
URL: https://github.com/maxlinde/baymedr
NeedsCompilation: no
Materials: README
CRAN checks: baymedr results

Downloads:

Reference manual: baymedr.pdf
Vignettes: Introduction to baymedr
Package source: baymedr_0.1.0.tar.gz
Windows binaries: r-devel: baymedr_0.1.0.zip, r-devel-gcc8: baymedr_0.1.0.zip, r-release: baymedr_0.1.0.zip, r-oldrel: baymedr_0.1.0.zip
OS X binaries: r-release: baymedr_0.1.0.tgz, r-oldrel: baymedr_0.1.0.tgz

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