The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 13, Number 1 (2019), 321-339.
Joint mean and covariance modeling of multiple health outcome measures
Health exams determine a patient’s health status by comparing the patient’s measurement with a population reference range, a 95% interval derived from a homogeneous reference population. Similarly, most of the established relation among health problems are assumed to hold for the entire population. We use data from the 2009–2010 National Health and Nutrition Examination Survey (NHANES) on four major health problems in the U.S. and apply a joint mean and covariance model to study how the reference ranges and associations of those health outcomes could vary among subpopulations. We discuss guidelines for model selection and evaluation, using standard criteria such as AIC in conjunction with posterior predictive checks. The results from the proposed model can help identify subpopulations in which more data need to be collected to refine the reference range and to study the specific associations among those health problems.
Ann. Appl. Stat., Volume 13, Number 1 (2019), 321-339.
Received: July 2015
Revised: January 2018
First available in Project Euclid: 10 April 2019
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Niu, Xiaoyue; Hoff, Peter D. Joint mean and covariance modeling of multiple health outcome measures. Ann. Appl. Stat. 13 (2019), no. 1, 321--339. doi:10.1214/18-AOAS1187. https://projecteuclid.org/euclid.aoas/1554861651
- Supplement to “Joint mean and covariance modeling of multiple health outcome measures.”. Additional results, tables, and plots mentioned in the text are in the Supplemental Material.