Abstract:
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The Northern Manhattan Study (NOMAS) is a population-based study designed to evaluate the impact of medical, socio-economic, and other risk factors on the incidence of vascular disease in a multi-ethnic, stroke-free cohort, consisting of 3,298 participants recruited between 1993 and 2001. In NOMAS, building a reliable prediction model for plaque burden will lead to improved prediction of stroke outcome in distant future. Carotid plaque measurements for total plaque area and density were available via high-resolution B-mode ultrasounds in NOMAS. These plaque phenotypes (area and density) take on non-negative values, with a point mass at 0 for subjects who did not have a plaque. In this application, we propose quantile regression model for zero-inflated, non-negative data. The quantile regression provides a natural modeling framework for non-normal data, and offers a semi-parametric approach that allows for robust prediction.
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