stabilise_re {stabiliser}

stabilise_re

Description

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

Arguments

data

A dataframe containing an outcome variable to be permuted.

outcome

The outcome as a string (i.e. "y").

level_2_id

The variable name determining level 2 status as a string (i.e., "level_2_column_name").

n_top_filter

The number of variables to filter for final model (Default = 50).

boot_reps

The number of bootstrap samples. Default is "auto" which selects number based on dataframe size.

permutations

The number of times to be permuted per repeat. Default is "auto" which selects number based on dataframe size.

perm_boot_reps

The number of times to repeat each set of permutations. Default is 20.

normalise

Normalise numeric variables (TRUE/FALSE)

dummy

Create dummy variables for factors/characters (TRUE/FALSE)

impute

Impute missing data (TRUE/FALSE)

Value

A list containing a table of variable stabilities and a numeric permutation threshold.