bmscstan: Bayesian Multilevel Single Case Models using 'Stan'

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>.

Version: 1.0.0
Depends: R (≥ 3.5.0), rstan, logspline, bayesplot, LaplacesDemon, ggplot2
Imports: coda
Suggests: reshape2, gridExtra, loo, mcmcse, bridgesampling, testthat, knitr, rmarkdown
Published: 2020-09-07
Author: Michele Scandola [aut, cre]
Maintainer: Michele Scandola <michele.scandola at univr.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: bmscstan citation info
Materials: README
CRAN checks: bmscstan results

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Reference manual: bmscstan.pdf
Vignettes: Fitting Bayesian Multilevel Single Case models using bmscstan
Package source: bmscstan_1.0.0.tar.gz
Windows binaries: r-devel: bmscstan_1.0.0.zip, r-release: bmscstan_1.0.0.zip, r-oldrel: bmscstan_1.0.0.zip
macOS binaries: r-release: bmscstan_1.0.0.tgz, r-oldrel: bmscstan_1.0.0.tgz

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