JSM 2004 Online Program

Abstract #301153

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Activity Number:	81
Type:	Contributed
Date/Time:	Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor:	Section on Risk Analysis
Abstract - #301153
Title:	The Partial Regression Approach to Fit GAMs in Air Pollution Research
Author(s):	Shui He*+ and Sati Mazumdar and Vincent C. Arena
Companies:	University of Pittsburgh and University of Pittsburgh and University of Pittsburgh
Address:	303 Parran Hall Dept. of Biostatistics, Pittsburgh, PA, 15261,
Keywords:	generalized additive model ; partial residual ; air pollution ; time series
Abstract:	Generalized Additive Models (GAMs) in S-plus, the most common statistical approach in time-series studies of air pollution and health, can seriously overestimate the fitted model parameters and underestimate their variances in the presence of concurvity. We present an alternate way to fit GAM to this type of data using partial residuals. Our simulation study indicates that this method gives better slope and corresponding variance estimates compared to the standard approach.

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