Bayesian statistical models for community annoyance survey data
| Autor: | Jasme Lee, Jonathan Rathsam, Alyson G. Wilson |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
education.field_of_study
Models Statistical Acoustics and Ultrasonics Computer science Multilevel model Bayesian probability Population Bayes Theorem Pilot Projects Statistical model Annoyance Sample (statistics) Environmental Exposure Ordinal regression Arts and Humanities (miscellaneous) Noise Transportation Surveys and Questionnaires Statistics Humans Survey data collection education |
| Zdroj: | The Journal of the Acoustical Society of America. 147:2222-2234 |
| ISSN: | 0001-4966 |
| DOI: | 10.1121/10.0001021 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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