About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Adjust supplied p-values for multiple comparisons.
npm install @stdlib/stats-padjustAlternatively,
- To load the package in a website via a
scripttag without installation and bundlers, use the ES Module available on theesmbranch (see README). - If you are using Deno, visit the
denobranch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umdbranch (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.
var padjust = require( '@stdlib/stats-padjust' );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 ]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 ]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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
