stabilise_re

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

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

stabilise_re 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>level_2_id</dt>
<dd>The variable name determining level 2 status as a string (i.e., "level_2_column_name").</dd>
<dt>n_top_filter</dt>
<dd>The number of variables to filter for final model (Default = 50).</dd>
<dt>boot_reps</dt>
<dd>The number of bootstrap samples. Default is "auto" which selects number based on dataframe size.</dd>
<dt>permutations</dt>
<dd>The number of times to be permuted per repeat. Default is "auto" which selects number based on dataframe size.</dd>
<dt>perm_boot_reps</dt>
<dd>The number of times to repeat each set of permutations. Default is 20.</dd>
<dt>normalise</dt>
<dd>Normalise numeric variables (TRUE/FALSE)</dd>
<dt>dummy</dt>
<dd>Create dummy variables for factors/characters (TRUE/FALSE)</dd>
<dt>impute</dt>
<dd>Impute missing data (TRUE/FALSE)</dd></dl>

Arguments

stabilise_re — stabilise_re

<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>level_2_id</dt>
<dd>The variable name determining level 2 status as a string (i.e., "level_2_column_name").</dd>


<dt>n_top_filter</dt>
<dd>The number of variables to filter for final model (Default = 50).</dd>


<dt>boot_reps</dt>
<dd>The number of bootstrap samples. Default is "auto" which selects number based on dataframe size.</dd>


<dt>permutations</dt>
<dd>The number of times to be permuted per repeat. Default is "auto" which selects number based on dataframe size.</dd>


<dt>perm_boot_reps</dt>
<dd>The number of times to repeat each set of permutations. Default is 20.</dd>


<dt>normalise</dt>
<dd>Normalise numeric variables (TRUE/FALSE)</dd>


<dt>dummy</dt>
<dd>Create dummy variables for factors/characters (TRUE/FALSE)</dd>


<dt>impute</dt>
<dd>Impute missing data (TRUE/FALSE)</dd>

</dl>

stabilise_re: stabilise_re

Description

Value

Arguments