Abstract #302226

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JSM 2003 Abstract #302226
Activity Number: 53
Type: Contributed
Date/Time: Sunday, August 3, 2003 : 4:00 PM to 5:50 PM
Sponsor: Section on Bayesian Stat. Sciences
Abstract - #302226
Title: Hierarchical Joined-Line Segments for Predicting Ovulation in Women
Author(s): Tanzy M. Love*+ and Julia A. Norton
Companies: Iowa State University and California State University
Address: Dept. of Statistics, Ames, IA, 50011,
Keywords: Hierarchical Bayesian ; ovulation prediction ; joined-line segments
Abstract:

There are many instances where a prediction for the date of ovulation in women is desired. It can be related to hormone levels in the blood and to physical changes in the woman. The urinary estrogen levels and the mucous viscosity are two easily measured covariates which can be used to predict the date of ovulation. We employed Heirarchical Bayesian Analysis using a joined-line segment model proposed by a biologist and estimated using MCMC as implemented in BUGS. One difficulty of this model is that the variable of interest is a join-point. The data come from Dr. Janet MacArthur of Massachusetts General Hospital. This data provide several complications, such as missing data from late starts and varied cycle lengths for different women.


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