boot_model

Function to calculate stability of variables' association with an outcome for a given model over a number of bootstrap repeats

internal

A stable approach to variable selection through stability selection and the use of a permutation-based objective stability threshold. Lima et al (2021) <doi:10.1038/s41598-020-79317-8>, Meinshausen and Buhlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>.

Robert Hyde

stabiliser

Stabilising Variable Selection

Martin Green

Eliana Lima

boot_model function

<dl><dt>data</dt>
<dd>a dataframe containing an outcome variable to be permuted</dd>
<dt>outcome</dt>
<dd>the outcome as a string (i.e. "y")</dd>
<dt>boot_reps</dt>
<dd>the number of bootstrap samples</dd>
<dt>model</dt>
<dd>the model to be used (i.e. model_mbic)</dd></dl>

Arguments

boot_model — boot_model

<dl>

<dt>data</dt>
<dd>a dataframe containing an outcome variable to be permuted</dd>


<dt>outcome</dt>
<dd>the outcome as a string (i.e. "y")</dd>


<dt>boot_reps</dt>
<dd>the number of bootstrap samples</dd>


<dt>model</dt>
<dd>the model to be used (i.e. model_mbic)</dd>

</dl>

boot_model: boot_model

Description

Arguments