Changepoint Tests Designed for the Analysis of Hiring Data Arising in Employment Discrimination Cases
针对就业歧视投诉前后招聘数据的变化，提出了基于累积和的变点检验方法，适用于二项分布和超几何分布数据，并通过模拟计算p值，为法院判断歧视责任提供统计依据。
Abstract When a complaint of discrimination is made, an employer may respond by hiring more minorities. From a legal viewpoint, the practices in effect during the time period prior to the complaint are more relevant for determining liability than those of the postcharge period. In Gay v. Waiters, the trial judge observed that the data suggested that a change occurred after the charge was filed. Because the data had not been subject to a formal statistical analysis, the court was reluctant to base its decision on this observation. Gastwirth and Freidlin and Gastwirth proposed cumulative-sum-based procedures for the analysis of hiring data following the binomial model. In this article, the procedures are extended to data following the hypergeometric model and to analysis of stratified data. Several datasets that were submitted to the courts in the United States are analyzed by the proposed methods. Because the data are usually reported by year, the ordinary large-sample theory is not sufficiently accurate. Therefore, we obtain the p values of the statistics by simulation. For binomial data, recent improvements in the Bonferroni inequality are used to derive a new upper bound. KEY WORDS: Binomial dataChangepointFair hiring practicesHypergeometric data