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Activity Number:
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289
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Type:
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Invited
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Date/Time:
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Wednesday, August 11, 2004 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #300125 |
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Title:
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Assessing the Effects of Reproductive Hormone Profiles on Bone Mineral Density Using Functional Two-stage Mixed Models
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Author(s):
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Daowen Zhang*+
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Companies:
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North Carolina State University
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Address:
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Dept. of Statistics, Raleigh, NC, 27696-8203,
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Keywords:
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longitudinal covariates ; mixed effects models ; nonparametric regression ; periodic smoothing splines ; REML
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Abstract:
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In the Study of Women's Health Across the Nation (SWAN), total hip bone mineral density (BMD) was measured together with daily levels of creatinine-adjusted follicle stimulating hormone (FSH) in urine over one menstrual cycle on more than 600 women. It is of scientific interest to investigate the effect of the FSH time profile on the total hip BMD, adjusting for age and body mass index. The statistical analysis is challenged by the complex data structure and tremendous among- and within-woman variation. We propose a measurement error partial functional linear model, where FSH measures are modeled using functional mixed effects models and the effect of the FSH time profile on BMD is modeled using a partial functional linear model by treating the unobserved true woman-specific FSH time profile as a functional covariate. We develop a two-stage estimation procedure using periodic smoothing splines. A key feature of our approach is that estimation at both stages could be conveniently cast into a unified mixed model framework. A simple test for constant functional covariate effect is also proposed. The proposed method is evaluated using simulation studies and applied to the SWAN data.
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