JSM 2005 - Toronto

Abstract #302330

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 436
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #302330
Title: Detecting Pulsatile Hormone Secretions Using Nonlinear Mixed Effects Partial Spline Models
Author(s): Yuedong Wang*+ and Yu-Chieh Yang and Anna Liu
Companies: University of California, Santa Barbara and National Taichung Institute of Technology and University of Massachusetts
Address: Department of Statistics and Applied Probability, Santa Barbara, CA, 93106,
Keywords: hormone data ; model selection ; random effects ; semi-parametric nonlinear mixed effects model ; shrinkage ; smoothing spline
Abstract:

The identification of episodic releases of hormonal pulse signals constitutes a major emphasis of endocrine investigation. Estimating the number, temporal locations, secretion rate, and elimination rate from hormone concentration measurements is of critical importance in endocrinology. In this talk, we present a new flexible statistical method for pulse detection based on nonlinear mixed effects partial spline models. We investigate biological variation between pulses using random effects. Pooling information from different pulses provides more efficient and stable estimation for parameters of interest. We combine all nuisance parameters, including a nonconstant basal secretion rate, and biological variations into a baseline function that is modeled nonparametrically using smoothing splines. We develop model selection and parameter estimation methods for the general nonlinear mixed effects partial spline models. We evaluate performance and the benefit of shrinkage by simulations and apply our methods to data from a medical experiment. We also present a R package for pulse detection and estimation.

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Revised March 2005