stabilise {stabiliser}

stabilise

Description

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

Arguments

data

A dataframe containing an outcome variable to be permuted.

outcome

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

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.

models

The models to select for stabilising. Default is elastic net (models = c("enet")), other available models include "lasso", "mbic", "mcp".

type

The type of model, either "linear" or "logistic"

quantile

The quantile of null stabilities to use as a threshold.

normalise

Normalise numeric variables (TRUE/FALSE)

dummy

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

impute

Impute missing data (TRUE/FALSE)

Value

A list for each model selected. Each list contains a dataframe of variable stabilities, a numeric permutation threshold, and a dataframe of coefficients for both bootstrap and permutation.