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Longitudinal Data Analysis and Time Series
Johns Hopkins University, Dept. of Biostatistics Working Papers
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Underestimation Of Standard Errors In Multi-Site Time Series Studies, Michael Daniels, Francesca Dominici, Scott L. Zeger
Underestimation Of Standard Errors In Multi-Site Time Series Studies, Michael Daniels, Francesca Dominici, Scott L. Zeger
Johns Hopkins University, Dept. of Biostatistics Working Papers
Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity.
Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to …