Fine Particles Survive Another Model

BrooklynDodger remains concerned that the fine particle community epidemiology findings are based on complex statistical models which are black boxes to everyone but the investigators and a small group of fellow modelers. The Dodger was plead that two new authors, neither Schwartz or Samet, attacked the same data base with two different models and found the same result.

In this paper, the authors use two flexible versions of distributed lag models to control extensively for the confounding effects of weather and season. The authors conduct a comprehensive sensitivity analysis of the particulate matter–mortality relation by applying these methods to the recently updated National Morbidity, Mortality, and Air Pollution Study database that comprises air pollution, weather, and mortality time series from 1987 to 2000 for 100 US cities. They conclude that, within the broad classes of models considered, national average estimates of particulate matter relative risk are consistent with previous estimates from this study and are robust to model specification for weather and seasonal confounding.

American Journal of Epidemiology 2005 162(1):80-88; doi:10.1093/aje/kwi157

Are the Acute Effects of Particulate Matter on Mortality in the National Morbidity, Mortality, and Air Pollution Study the Result of Inadequate Control for Weather and Season? A Sensitivity Analysis using Flexible Distributed Lag Models

Leah J. Welty and Scott L. Zeger
From the Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD