Analysis of Multiple Biomarkers Using Structural Equation Modeling.

ABSTRACT:

Objectives

When examining the relationship between smoking intensity and toxicant exposure biomarkers in an effort to understand the potential risk for smoking-related disease, individual biomarkers may not be strongly associated with smoking intensity because of the inherent variability in biomarkers. Structural equation modeling (SEM) offers a powerful solution by modeling the relationship between smoking intensity and multiple biomarkers through a latent variable.

Methods

Baseline data from a randomized trial (N = 1250) were used to estimate the relationship between smoking intensity and a latent toxicant exposure variable summarizing five volatile organic compound biomarkers. Two variables of smoking intensity were analyzed: the self-report cigarettes smoked per day and

SUBMITTER: Cao W 

PROVIDER: S-EPMC9075702 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature