An Application of Bayesian Regression in Ergonomics
Document Type
Conference Proceeding
Publication Date
7-1-2020
Publication Title
International Conference on Applied Human Factors and Erogonomics
Publisher
Springer
Publisher Location
San Diego, CA
Volume
1217
First page number:
367
Last page number:
376
Abstract
Statistics plays an important part in almost all disciplines, including applied ergonomics and human factors. Majority of applied ergonomics literature uses the classical or frequentist statistical methods, and the applications of Bayesian statistical methods in applied ergonomics has been quite limited. This is possibly due to two reasons: (i) the discipline of applied ergonomics is relatively new, dating back to WWI, and (ii) computationally intensive nature of Bayesian solutions. In other disciplines, Bayesian statistical methods have become quite popular. The purpose of this article is to introduce Bayesian regression modeling to the research area of applied ergonomics, via a dataset from ergonomics research.
Keywords
Ordinal regression; Proportional odds assumption; Weekly informative prior; Prior distribution; Posterior distribution; HPD credible sets; Markov chain monte carlo simulation
Disciplines
Applied Statistics | Biostatistics | Ergonomics
Language
English
Repository Citation
Singh, A. K.,
Dalpatadu, R. J.
(2020).
An Application of Bayesian Regression in Ergonomics.
International Conference on Applied Human Factors and Erogonomics, 1217
367-376.
San Diego, CA: Springer.
http://dx.doi.org/10.1007/978-3-030-51828-8_47