prop_na {structToolbox} | R Documentation

## Fisher's exact test for missing values

### Description

A Fisher's exact test is used to compare the number of missing values in each group. Multiple test corrected p-values are computed to indicate whether there is a significant difference in the number of missing values across groups for each feature.

### Usage

    prop_na(alpha = 0.05, mtc = "fdr", factor_name, ...)

### Arguments

`alpha` | (numeric) The p-value cutoff for determining significance. The default is `0.05`.
`mtc` | (character) Multiple test correction method. Allowed values are limited to the following: `"bonferroni"`: Bonferroni correction in which the p-values are multiplied by the number of comparisons. `"fdr"`: Benjamini and Hochberg False Discovery Rate correction. `"none"`: No correction. The default is `"fdr"`.
`factor_name` | (character) The name of a sample-meta column to use.
`...` | Additional slots and values passed to `struct_class`.

### Value

A `prop_na` object with the following `output` slots:

`p_value` | (data.frame) The probability of observing the calculated statistic.
`significant` | (data.frame) TRUE if the calculated p-value is less than the supplied threshold (alpha).
`na_count` | (data.frame) The number of NA values per group of the chosen factor.

struct object

### Examples

    M = prop_na(factor_name='Species')

[Package structToolbox version 1.6.1 Index]