Special Issue Paper

A Bayesian order-restricted model for hormonal dynamics during menstrual cycles of healthy women

  1. Anindya Roy1,*,
  2. Michelle Danaher1,2,
  3. Sunni L. Mumford2,
  4. Zhen Chen2

Article first published online: 7 DEC 2011

DOI: 10.1002/sim.4419

Issue

Statistics in Medicine

Statistics in Medicine

Special Issue: Biomarker Working Group: Issues in the Design and Analysis of Epidemiological Studies with Biomarkers

Volume 31, Issue 22, pages 2428–2440, 28 September 2012

Additional Information

How to Cite

Roy, A., Danaher, M., Mumford, S. L. and Chen, Z. (2012), A Bayesian order-restricted model for hormonal dynamics during menstrual cycles of healthy women. Statist. Med., 31: 2428–2440. doi: 10.1002/sim.4419

Author Information

  1. 1

    Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, MD, USA

  2. 2

    Division of Epidemiology, Statistics and Prevention Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Rockville, MD, USA

* Anindya Roy, Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, MD 21250, USA.
E-mail: anindya@umbc.edu

Publication History

  1. Issue published online: 11 SEP 2012
  2. Article first published online: 7 DEC 2011
  3. Manuscript Accepted: 1 SEP 2011
  4. Manuscript Received: 16 JAN 2011

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Keywords:

  • Gibbs sampling;
  • parameter constraints;
  • quadratic programming;
  • reproductive hormones;
  • oxidative stress

We propose a Bayesian framework for analyzing multivariate linear mixed effect models with linear constraints on the fixed effect parameters. The procedure can incorporate both firm and soft restrictions on the parameters and Bayesian model selection for the random effects. The framework is used to analyze data from the BioCycle study. One of the main objectives of the BioCycle study is to investigate the association between markers of oxidative stress and hormone levels during menstrual cycles of healthy women. Contrary to the popular belief that ovarian hormones are negatively associated with level of F 2-isoprostanes, a known marker for oxidative stress, our analysis finds a positive association between ovarian hormone levels and isoprostane levels. The positive association corroborates the findings from a previous analysis of the BioCycle data. Copyright © 2011 John Wiley & Sons, Ltd.

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