ftestEvidence

Justify your alpha level by avoiding the Lindley paradox or aiming for moderate or strong evidence when using anova.

Functions to justify alpha levels for statistical hypothesis tests by avoiding Lindley's paradox, or by minimizing or balancing error rates. For more information about the package please read the following: Maier & Lakens (2021) <doi:10.31234/osf.io/ts4r6>).

Maximilian Maier

JustifyAlpha

Justifying Alpha Levels for Hypothesis Tests

Daniel Lakens

ftestEvidence function

<dl><dt>evidence</dt>
<dd>Desired level of evidence: "Lindley" to avoid the Lindley Paradox, "moderate" to achieve moderate evidence and "strong" to achieve strong evidence.
Users that are more familiar with Bayesian statistics can also directly enter their desired Bayes factor.</dd>
<dt>df1</dt>
<dd>Numerator degrees of freedom.</dd>
<dt>df2</dt>
<dd>Denominator degrees of freedom.</dd>
<dt>paired</dt>
<dd>If true a within subjects design is assumed.</dd>
<dt>printplot</dt>
<dd>If true prints a plot relating Bayes factors and p-values.</dd></dl>

Arguments

Justify your alpha level by avoiding the Lindley paradox or aiming for moderate or strong evidence when using anova. — ftestEvidence

<dl>

<dt>evidence</dt>
<dd>Desired level of evidence: "Lindley" to avoid the Lindley Paradox, "moderate" to achieve moderate evidence and "strong" to achieve strong evidence.
Users that are more familiar with Bayesian statistics can also directly enter their desired Bayes factor.</dd>


<dt>df1</dt>
<dd>Numerator degrees of freedom.</dd>


<dt>df2</dt>
<dd>Denominator degrees of freedom.</dd>


<dt>paired</dt>
<dd>If true a within subjects design is assumed.</dd>


<dt>printplot</dt>
<dd>If true prints a plot relating Bayes factors and p-values.</dd>

</dl>

ftestEvidence: Justify your alpha level by avoiding the Lindley paradox or aiming for moderate or strong evidence when using anova.

Description

Usage

Value

Arguments

References

Examples