Joint mean and covariance modeling of multiple health outcome measures

Xiaoyue Niu, Peter D. Hoff

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)321-339
Number of pages19
JournalAnnals of Applied Statistics
Volume13
Issue number1
DOIs
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty

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