Analyzing chromatographic data using multilevel modeling

Volume: 410, Issue: 16, Pages: 3905 - 3915
Published: Apr 21, 2018
Abstract
It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of...
Paper Details
Title
Analyzing chromatographic data using multilevel modeling
Published Date
Apr 21, 2018
Volume
410
Issue
16
Pages
3905 - 3915
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.