This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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360
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #308396 |
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Title:
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On the Modeling and Simulation of Ambulatory Blood Pressure Traces
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Author(s):
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David A. James*+ and Xiaoyong Sun
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Companies:
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Novartis and Iowa State University
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Address:
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One Health Plaza, East Hanover, NJ, 07936,
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Keywords:
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ambulatory blood pressure ;
mixed-effects ;
cosinor ;
smoothing ;
local likelihood ;
chronobiology
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Abstract:
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We illustrate parametric and non-parametric methods for the exploration, modeling, and simulation of ambulatory blood pressure measurement (ABPM) curves. ABPM is a minimally invasive blood pressure monitoring tool that consists of a portable device that records subjects' blood pressure every 10-30 minutes over one or more days on multiple occasions during the course of a clinical study. These data are subject to additional sources variations that need to be statistically accounted in order to properly assess the time-course of medical features such as trough-to-peak ratios, "dipping" status, morning surge, etc. Models we consider include chronobiology-based cosinor models, linear and non-linear mixed effects, local-liklihood regression (Loader, 1999), loess smoothing (Cleveland 1979), and generalized additive models (Hastie and Tibshirani, 1990).
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