calc_anchor.cs_anchor_group_within

This is an internal function and should never be called directly.

internal

A clinical significance analysis can be used to determine if an
intervention has a meaningful or practical effect for patients. You provide
a tidy data set plus a few more metrics and this package will take care of
it to make your results publication ready. Accompanying package to
Claus et al. <doi:10.18637/jss.v111.i01>.

Benedikt Claus

clinicalsignificance

A Toolbox for Clinical Significance Analyses in Intervention
Studies

calc_anchor.cs_anchor_group_within function

<dl><dt>bayesian</dt>
<dd>Logical, if Bayesian tests and uncertainty intervals should
be used, defaults to <code>TRUE</code>.</dd>
<dt>prior_scale</dt>
<dd>String or numeric, can be adjusted to change the Bayesian
prior distribution. See the documentation for <code>rscale</code> in
<code>BayesFactor::ttestBF()</code> for details</dd></dl>

Arguments

Anchor Calculations for Group Effect Within — calc_anchor.cs_anchor_group_within

<dl>

<dt>bayesian</dt>
<dd>Logical, if Bayesian tests and uncertainty intervals should
be used, defaults to <code>TRUE</code>.</dd>


<dt>prior_scale</dt>
<dd>String or numeric, can be adjusted to change the Bayesian
prior distribution. See the documentation for <code>rscale</code> in
<code>BayesFactor::ttestBF()</code> for details</dd>

</dl>

calc_anchor.cs_anchor_group_within: Anchor Calculations for Group Effect Within

Description

Usage

Arguments