title: A Bayesian order-restricted model for hormonal dynamics during menstrual cycles of healthy women.
abstract: 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.
authors.affiliation: Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, MD 21250, USA. anindya@umbc.edu
authors.forename: Anindya
authors.initials: A
authors.lastname: Roy
authors.forename: Michelle
authors.initials: M
authors.lastname: Danaher
authors.forename: Sunni L
authors.initials: SL
authors.lastname: Mumford
authors.forename: Zhen
authors.initials: Z
authors.lastname: Chen
mesh_terms: D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D004967:Estrogens / Q000502:physiology; D005260:Female; D005640:Follicle Stimulating Hormone / Q000502:physiology; D006801:Humans; D028421:Isoprostanes / Q000502:physiology; D007986:Luteinizing Hormone / Q000502:physiology; D008597:Menstrual Cycle / Q000502:physiology*; D015233:Models, Statistical; D018384:Oxidative Stress / Q000502:physiology; D055815:Young Adult
chemical_list: D004967:Estrogens; D028421:Isoprostanes; D007986:Luteinizing Hormone; D005640:Follicle Stimulating Hormone