Latent variable model: Difference between revisions

Revision as of 13:15, 26 June 2019

Revision as of 13:54, 28 July 2019

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Because the distribution of a continuous latent variable can be approximated by a discrete distribution, the distinction between continuous and discrete variables turns out not to be fundamental at all. Therefore, there may be a psychometrical latent variable, but not a [[psychology|psychological]] psychometric variable.

Recently DSDs and Latent Variable modeling were applied for the first time to the optimization of an extraction procedure in order to analyze target compounds present in wine samples. Latent Variable modeling can be a relevant tool for the optimization of analytical techniques, contributing to the implementation of rigorous, systematic and more efficient optimization protocols. <ref>{{Cite webjournal|url=https:|doi=10.1016//wwwj.sciencedirectchemolab.2018.com/science/article/pii/S016974391830094706.010|title=Definitive Screening Designs and latent variable modelling for the optimization of solid phase microextraction (SPME): Case study - Quantification of volatile fatty acids in wines|website=www.sciencedirect.com|access-date=2018-07-03}}</ref>

==See also==