@article{ref1,
title="Modeling drinking behavior progression in youth: a non-identified probability discrete event system using cross-sectional data",
journal="Current HIV research",
year="2015",
author="Hu, Xingdi and Chen, Xinguang and Cook, Robert L. and Chen, Ding-Geng and Okafor, Chukwuemeka",
volume="14",
number="2",
pages="93-100",
abstract="The probabilistic discrete event systems (PDES) model is a promising approach to study longitudinal dynamics of underage drinking using cross-sectional data. However, the utility of this approach is limited because the constructed PDES model is often non-identifiable and thereby insolvable. This limitation can be overcome by applying the Moore-Penrose (M-P) generalized inverse matrix method. To demonstrate its application, we developed a PDES model of drinking behavior consisted of four progression stages, including never-drinker (ND), light/moderate-drinker (LMD), heavy-drinker (HD), and ex-drinker (XD), all being linked with 13 possible transition paths. We tested the model with data for participants aged 12-21 years from the 2012 National Survey on Drug Use and Health (NSDUH). Annual transitional probabilities by age groups for the 13 drinking progression pathways were successfully estimated with the M-P generalized inverse matrix approach. Result from the analysis indicated an inverse &quot;J&quot; shape curve characterizing the pattern of experimental use of alcohol from adolescence to young adulthood. We also observed a dramatic increase for the initiation of LMD and HD after age 18 and a sharp decline afterwards in quitting for both LMD and HD. These findings are consistent with the developmental perspective regarding the dynamics of underage drinking. The M-P approach we tested in this study will facilitate the use of the PDES approach to examine many health behaviors with the widely available cross-sectional data.<p /> <p>Language: en</p>",
language="en",
issn="1570-162X",
doi="",
url="http://dx.doi.org/"
}