Modeling Menstrual Cycle Lengths at the Approach of Menopause Using Bayesian Change Point Models

• Activity Number: 600
• Type: Contributed
• Date/Time: Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Xiaobi Huang*+ and Michael Elliott
• Companies: University of Michigan and University of Michigan
• Keywords: Multiple Imputation ; Final Menstrual Period ; Age of Menarche ; Parity ; TREMIN

Abstract

As women approach menopause, the patterns of their menstruation segment lengths change. In order to study when changes in menstrual length happen, we build Bayesian linear change point model to model the mean segment length as well as the variability of the length. The full model includes separate linear change points for each woman and a hierarchical model to link them together, along with regression components to include predictors of menopausal onset such as age at menarche and parity. Data are from TREMIN, an ongoing 70-year-old longitudinal study that has obtained menstrual calendar data of women throughout their life course. Our study cohort include nearly 1000 women, many of whom have missingness due to hormone use, surgery, random missingness and loss of contact. We integrate multiple imputation in our Bayesian estimation procedure to deal with different forms of the missingness.