Comparison of Two Statistical Models for Low Boom Dose-response Relationships with Correlated Responses

This study compares two statistical models to construct summary dose-response curves for low boom
community noise surveys. Data from two NASA field surveys are used that consist of multiple responses
per survey participant. These data require an approach that accounts for the correlation among repeated
annoyance observations from the same participant. A multilevel model accounts for the correlation by
allowing estimated parameters to vary with each survey participant. On the other hand, a population
average model utilizes generalized estimating equations and accounts for the correlation via a userspecified
within-subject correlation structure. A visual comparison of the dose-response curves for these
two methods reveals similar results. When comparing specific points along the summary curves, the
multilevel model yields more precise confidence bounds than the population average model. The similarity
between the summary curves derived from each model lends validity to both approaches for approximating
a population representative summary curve, though modeling assumptions may lend favor to the multilevel
logistic modeling approach over the population average model.