SOME METHODS TO ADDRESS COLLINEARITY AMONG POLLUTANTS IN EPIDEMIOLOGICAL TIME SERIES

The aim of this paper is to provide accurate estimation methods for regression models used in epidemiological time series to deduce quantitative morbidity relationships. Such models often include highly correlated variables (pollutant levels and climatic conditions) as well as lagged and unlagged va...

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Bibliographic Details
Published in:Statistics in medicine 1997-03, Vol.16 (5), p.527-544
Main Authors: PITARD, A., VIEL, J. F.
Format: Article
Language:English
Subjects:
Bias
Biological and medical sciences
Climate
Computerized, statistical medical data processing and models in biomedicine
Data Interpretation, Statistical
Environmental Pollutants
Epidemiologic Methods
Humans
Medical sciences
Medical statistics
Morbidity
Regression Analysis
Reproducibility of Results
Stochastic Processes
Time Factors
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Summary:The aim of this paper is to provide accurate estimation methods for regression models used in epidemiological time series to deduce quantitative morbidity relationships. Such models often include highly correlated variables (pollutant levels and climatic conditions) as well as lagged and unlagged values of the same variables (which also show a high collinearity due to the stochastic dependency of consecutive measurements). We first describe some methods to detect and assess multicollinearity. We recall the drawbacks of usual methods of estimation, and then after briefly mentioning traditional solutions, we explore three alternative methods accounting for multicollinearity: Sclove's estimation; Almon's method; and a combination of Almon's method and principal components procedure. We compare these methods in obtaining efficient estimators on environmental epidemiological data (children's hospital admissions as dependent variable and unlagged and lagged values of outdoor temperature, SO2, NO and CO as explanatory variables). © 1997 by John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/(SICI)1097-0258(19970315)16:5<527::AID-SIM429>3.0.CO;2-C