A Simulation Study of Confounding in Generalized Linear Models for Air Pollution Epidemiology

Confounding between the model covariates and causal variables (which may or may not be included as model covariates) is a well-known problem in regression models used in air pollution epidemiology. This problem is usually acknowledged but hardly ever investigated, especially in the context of genera...

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Veröffentlicht in:	Environmental health perspectives 1999-03, Vol.107 (3), p.217-222
Hauptverfasser:	Chen, Colin, Chock, David P., Winkler, Sandra L.
Format:	Artikel
Sprache:	eng
Schlagworte:	Air pollution Air Pollution - statistics & numerical data Air quality Bias Coefficients Computer Simulation Confidence Intervals Confounding Factors (Epidemiology) Correlation coefficients Data Interpretation, Statistical Datasets Environmental Exposure - statistics & numerical data Linear Models Linear regression Mortality Particulate matter Regression analysis Research Design - standards Sample Size
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