R: Generate 'n' permutation replicates.

permute {modelr} | R Documentation

## Generate `n` permutation replicates.

### Description

A permutation test involves permuting one or more variables in a data set before performing the test, in order to break any existing relationships and simulate the null hypothesis. One can then compare the true statistic to the generated distribution of null statistics.

### Usage

    permute(data, n, ..., .id = ".id")

    permute_(data, n, columns, .id = ".id")

### Arguments

`data` | A data frame
`n` | Number of permutations to generate.
`...` | Columns to permute. This supports bare column names or dplyr select_helpers.
`.id` | Name of variable that gives each model a unique integer id.
`columns` | In `permute_`, vector of column names to permute.

### Value

A data frame with `n` rows and one column: `perm`

### Examples

    library(purrr)
    perms <- permute(mtcars,  1000, mpg)

    models <- map(perms$perm, ~ lm(mpg ~ wt, data = .))
    glanced <- map_df(models, broom::glance, .id = "id")

    # distribution of null permutation statistics
    hist(glanced$statistic)
    # confirm these are roughly uniform p-values
    hist(glanced$p.value)

    # test against the unpermuted model to get a permutation p-value
    mod <- lm(mpg ~ wt, mtcars)
    mean(glanced$statistic > broom::glance(mod)$statistic)

[Package modelr version 0.1.1 Index]