print.pairwise.BMSC

Print summaries of Pairwise Bayesian Multilevel Single Case objects

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>.

Michele Scandola

bmscstan

Bayesian Multilevel Single Case Models using 'Stan'

print.pairwise.BMSC function

<dl><dt>x</dt>
<dd>An object of class <code>pairwise.BMSC</code>, resulting from the pairwise.BMSC function.</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Print summaries of Pairwise Bayesian Multilevel Single Case objects — print.pairwise.BMSC

<dl>

<dt>x</dt>
<dd>An object of class <code>pairwise.BMSC</code>, resulting from the pairwise.BMSC function.</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

print.pairwise.BMSC: Print summaries of Pairwise Bayesian Multilevel Single Case objects

Description

Usage

Arguments