alphaN_plot

Creates a plot of alpha as function of sample size for each of the four prior options

Sets the alpha level for coefficients in a regression model
as a decreasing function of the sample size through the use of
Jeffreys' Approximate Bayes factor. You tell alphaN() your sample
size, and it tells you to which value you must lower alpha to avoid
Lindley's Paradox. For details, see Wulff and Taylor (2023)
<doi:10.31234/osf.io/3cbh7>.

Jesper Wulff

alphaN

Set Alpha Based on Sample Size Using Bayes Factors

Luke Taylor

alphaN_plot function

<dl><dt>BF</dt>
<dd>Bayes factor you would like to match. 1 to avoid Lindley's Paradox, 3 to achieve moderate evidence and 10 to achieve strong evidence.</dd>
<dt>max</dt>
<dd>The maximum number of sample size. Defaults to 10,000.</dd></dl>

Arguments

Creates a plot of alpha as function of sample size for each of the four prior options — alphaN_plot

<dl>

<dt>BF</dt>
<dd>Bayes factor you would like to match. 1 to avoid Lindley's Paradox, 3 to achieve moderate evidence and 10 to achieve strong evidence.</dd>


<dt>max</dt>
<dd>The maximum number of sample size. Defaults to 10,000.</dd>

</dl>

alphaN_plot: Creates a plot of alpha as function of sample size for each of the four prior options

Description

Usage

Value

Arguments

Examples