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padjust

Adjust supplied p-values for multiple comparisons.

Installation

npm install @stdlib/stats-padjust

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var padjust = require( '@stdlib/stats-padjust' );

padjust( pvals, method[, comparisons] )

Adjusts supplied p-values for multiple comparisons via a specified method.

var out = padjust( [ 0.1496, 0.0275, 0.3053, 0.1599, 0.2061 ], 'bonferroni' );
// returns [ 0.748, ~0.138, ..., ~0.799, 1 ]

The method parameter can be one of the following values:

• bh: Benjamini-Hochberg procedure controlling the False Discovery Rate (FDR).
• bonferroni: Bonferroni correction fixing the family-wise error rate by multiplying the p-values with the number of comparisons. The Bonferroni correction is usually a too conservative adjustment compared to the others.
• by: Procedure by Benjamini & Yekutieli for controlling the False Discovery Rate (FDR) under dependence.
• holm: Hommel's method controlling family-wise error rate. It is uniformly more powerful than the Bonferroni correction.
• hommel: Hommel's method, which is valid when hypothesis tests are independent. It is more expensive to compute than the other methods.

var pvalues = [ 0.319, 0.201, 0.4, 0.374, 0.113 ];
var out = padjust( pvalues, 'holm' );
// returns [ ~0.957, 0.804, ..., ~0.957, ~0.565 ]

out = padjust( pvalues, 'bh' );
// returns [ 0.4, 0.4, ..., 0.4, 0.4 ]

By default, the number of comparisons for which the p-values should be corrected is equal to the number of provided p-values. Alternatively, it is possible to set comparisons to a number greater than the length of pvals. In that case, the methods assume comparisons - pvals.length unobserved p-values that are greater than all observed p-values (for Holm's method and the Bonferroni correction) or equal to 1 for the remaining methods.

var pvalues = [ 0.319, 0.201, 0.4, 0.374, 0.113 ];
var out = padjust( pvalues, 'bh', 10 );
// returns [ 0.8, 0.8, ..., 0.8, 0.8 ]

Examples

var padjust = require( '@stdlib/stats-padjust' );

var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];

var out = padjust( pvalues, 'bh' );
// returns [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]

out = padjust( pvalues, 'bonferroni' );
// returns [ 0.04, 0.15, 0.615, 1.0, 1.0 ]

out = padjust( pvalues, 'by' );
// returns [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]

out = padjust( pvalues, 'holm' );
// returns [ 0.2, 0.6, 1.0, 1.0, 1.0 ]

out = padjust( pvalues, 'hommel' );
// returns [ 0.16, 0.6, 1.0, 1.0, 1.0 ]

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Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.