title: Development of a two-step indirect method for modeling Ecom50.
abstract: A novel approach is developed for modeling situations in which the modeled property is an algebraically transformed version of the original experimental data. In many cases such a transformation results in a data set with a significantly smaller data range. Here we explore the effects of range-of-data on modeling statistics. We illustrate a twostep method using data on the mass spectrometry collision energy (CE) that is required to decompose 50% of precursor ions to fragments (CE50). Earlier we showed that a nonlinear center-of-mass transformation, yielding Ecom50, produces values less dependent on the specific mass spectrometric experimental conditions. For this data set the Ecom50 range is 13.5% of the CE50 range. We propose a two-step modeling method. First, the original experimental data, CE50, (larger range-of-data) is modeled by a standard modeling method (PLS). Second, the calculated dependent variable resulting from the modeling is algebraically transformed (not modeled) according to the center-of-mass transformation, providing the generally more useful data, Ecom50. As shown here, use of this two-step method for predicting Ecom50 (from previously published data) produces a standard error 21% smaller and correspondingly reduces the confidence interval for prediction. Some specific implications for prediction are given for a published data set. This work is part of the ongoing development of a system of models to assist in the development of human metabolites.
authors.affiliation: Department of Chemistry, Eastern Nazarene College, 23 East Elm Avenue, Quincy, MA 02170, USA. lowell.hall@enc.edu.
authors.forename: Lowell H
authors.initials: LH
authors.lastname: Hall
authors.forename: L Mark
authors.initials: LM
authors.lastname: Hall
authors.forename: Dennis W
authors.initials: DW
authors.lastname: Hill
authors.forename: Douglas M
authors.initials: DM
authors.lastname: Hawkins
authors.forename: Ming-Hui
authors.initials: MH
authors.lastname: Chen
authors.forename: David F
authors.initials: DF
authors.lastname: Grant
mesh_terms: D006801:Humans; D013058:Mass Spectrometry; D015233:Models, Statistical