Public Data Resource

Interlab: A python module for consensus analysis in interlaboratory studies

Contact: David Sheen.

Identifier: doi:10.18434/T4/1503310

Described in these articles:

A scoring metric for multivariate data for reproducibility analysis using chemometric methods,

Classification of samples from NMR-based metabolomics using principal components analysis and partial least squares with uncertainty estimation

Version: 1.0...

A python module for consensus analysis in interlaboratory studies

Research Areas

NIST R&D: Information Technology: Software researchMathematics and Statistics

Keywords: interlaboratory studyuncertainty analysisoutlier detection

These data are public.

Data and related material can be found at the following locations:

Interlab

A python module for consensus analysis in interlaboratory studies

Sheen, D. A., Rocha, W. F. C., Lippa, K. A., & Bearden, D. W. (2017). A scoring metric for multivariate data for reproducibility analysis using chemometric methods. Chemometrics and Intelligent Laboratory Systems, 162, 10â20. https://doi.org/10.1016/j.chemolab.2016.12.010

Rocha, W. F. de C., Sheen, D. A., & Bearden, D. W. (2018). Classification of samples from NMR-based metabolomics using principal components analysis and partial least squares with uncertainty estimation. Analytical and Bioanalytical Chemistry, 410(24), 6305â6319. https://doi.org/10.1007/s00216-018-1240-2

Version: 1.0...

Cite this dataset

David Sheen (2018), Interlab: A python module for consensus analysis in interlaboratory studies, National Institute of Standards and Technology, https://doi.org/10.18434/T4/1503310 (Accessed 2025-07-17)

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