interlab: A Python Module for Analyzing Interlaboratory Comparison Data

• Published in: Journal of research of the National Institute of Standards and Technology Vol. 124; pp. 1 - 2
• Main Author: Sheen, David A
• Format: Journal Article
• Language: English
• Published: Gaithersburg National Institute of Standards and Technology 01.01.2019; Superintendent of Documents; [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology
• Subjects: Artificial intelligence; Chemical research; Chemometrics; Data analysis; Distribution functions; Equipment and supplies; Gloss; Laboratories; Mathematical analysis; NMR; Normal distribution; Nuclear magnetic resonance; Outliers (statistics); Population (statistical); Principal components analysis; Scientific software; Software; Spectra (Spectroscopy); Statistical analysis; Statistical methods; United States; United States > US
• ISSN: 2165-7254; 1044-677X; 2165-7254
• DOI: 10.6028/jres.124.006

interlab was developed as a software tool to perform consensus analysis on spectral data from interlaboratory studies. It is designed to estimate the spread in the spectral data and to identify possible outliers among both spectral populations and facilities in the study. Use of this code allows researchers to identify laboratories producing data closest to the consensus values, thereby ensuring that untargeted studies are using the most precise data available to them. The software was originally developed for analyzing NMR data but can be applied to any array data, including Raman or FTIR spectroscopy and GC-MS or LC-MS.