Analyse single case analyses against a control group. Its purpose is to provide a flexible, with good power and low first type error approach that can manage at the same time controls' and patient's data. The use of Bayesian statistics allows to test both the alternative and null hypothesis. Scandola, M., & Romano, D. (2020, August 3). <doi:10.31234/osf.io/sajdq> Scandola, M., & Romano, D. (2021). <doi:10.1016/j.neuropsychologia.2021.107834>.
Version: 1.2.1.0 Depends: R (≥ 3.5.0), rstan, ggplot2, bayesplot Imports: loo, logspline, LaplacesDemon Suggests: reshape2, gridExtra, bridgesampling, testthat, knitr, rmarkdown, covr Published: 2022-09-04 DOI: 10.32614/CRAN.package.bmscstan Author: Michele Scandola [aut, cre] Maintainer: Michele Scandola <michele.scandola at univr.it> BugReports: https://github.com/michelescandola/bmscstan License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/michelescandola/bmscstan NeedsCompilation: no Citation: bmscstan citation info Materials: README CRAN checks: bmscstan results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=bmscstan to link to this page.
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