Wilson Sara R, Leonard Robert D, Edwards David J, Swieringa Kurt A, Underwood Matt
National Aeronautics and Space Administration.
Virginia Commonwealth University.
Qual Eng. 2018;30(4):546-555. doi: 10.1080/08982112.2018.1482339. Epub 2018 Oct 18.
Poisson regression is a commonly used tool for analyzing rate data; however, the assumption that the mean and variance of a process are equal rarely holds true in practice. When this assumption is violated, a quasi-Poisson distribution can be used to account for the existing over- or under-dispersion. This paper presents an analysis of a study conducted by NASA to assess the performance of a new airborne spacing algorithm. A deterministic computer simulation was conducted to examine the algorithm in various conditions designed to simulate real-life scenarios, and two measures of algorithm performance were modeled using both continuous and categorical factors. Due to the presence of under-dispersion, tests for significance of main effects and two-factor interactions required bias adjustment. This paper presents a comparison of tests of effects for the Poisson and quasi-Poisson models, details of fitting these models using common statistical software packages, and calculation of dispersion tests.
泊松回归是分析速率数据常用的工具；然而，过程的均值和方差相等这一假设在实际中很少成立。当这一假设不成立时，可使用拟泊松分布来处理现有的过度离散或不足离散情况。本文对美国国家航空航天局（NASA）进行的一项评估新空中间距算法性能的研究进行了分析。进行了确定性计算机模拟，以在旨在模拟现实场景的各种条件下检验该算法，并使用连续和分类因素对算法性能的两个度量进行建模。由于存在不足离散，主效应和双因素交互作用的显著性检验需要进行偏差调整。本文比较了泊松模型和拟泊松模型的效应检验，详细介绍了使用常见统计软件包拟合这些模型的过程以及离散检验的计算。
