Bayesian Statistical Models for Community Annoyance Survey Data

• Published in: The Journal of the Acoustical Society of America Vol. 147; no. 4; pp. 2222 - 2234
• Main Authors: Lee, Jasme, Rathsam, Jonathan, Wilson, Alyson
• Format: Journal Article
• Language: English
• Published: Langley Research Center Acoustical Society of America 01.04.2020
• Subjects: Acoustics; Regression Analysis; Deviance Information Criterion; Statistical Mechanics Models; Shock Waves; Computer Simulation; Musical Instruments; General Procedures And Instrumentation; Acoustic Modeling; Simulation And Analysis; Aircraft; Statistical Models
• ISSN: 0001-4966; 1520-8524; 1520-8524
• DOI: 10.1121/10.0001021

This paper demonstrates the use of two Bayesian statistical models to analyze single-event sonic boom exposure and human annoyance data from community response surveys. Each model is fit to data from a NASA pilot study.Unlike many community noise surveys, this study used a panel sample to collect multiple observations per participant instead of a single observation. Thus, a multilevel (also known as hierarchical or mixed-effects) model is used to account for the within-subject correlation in the panel sample data. This paper describes a multilevel logistic regression model and a multilevel ordinal regression model. The paper also proposes a method for calculating a summary dose-response curve from the multilevel models that represents the population. The two models’ summary dose-response curves are visually similar. However, their estimates differ when calculating the noise dose at a fixed percent highly annoyed.