Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes.

ABSTRACT: Dietary assessment of episodically consumed foods gives rise to nonnegative data that have excess zeros and measurement error. Tooze et al. (2006, Journal of the American Dietetic Association 106, 1575-1587) describe a general statistical approach (National Cancer Institute method) for modeling such food intakes reported on two or more 24-hour recalls (24HRs) and demonstrate its use to estimate the distribution of the food's usual intake in the general population. In this article, we propose an extension of this method to predict individual usual intake of such foods and to evaluate the relationships of usual intakes with health outcomes. Following the regression calibration approach for measurement error correction, individual usual intake is generally predicted as the conditional mean in

SUBMITTER: Kipnis V 

PROVIDER: S-EPMC2881223 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature