UNDERSTANDING THE IMPACT OF TEST VALIDITY AND BIAS ON SELECTION ERRORS AND ADVERSE IMPACT IN HUMAN RESOURCE SELECTION
提出了一个整合框架，揭示测试效度、测试偏差、选拔错误和不利影响之间的关系，并首次定义了偏差导致的选拔错误，为HR从业者提供量化分析工具。
We propose an integrative framework for understanding the relationship among 4 closely related issues in human resource (HR) selection: test validity, test bias, selection errors, and adverse impact. One byproduct of our integrative approach is the concept of a previously undocumented source of selection errors we call bias‐based selection errors (i.e., errors that arise from using a biased test as if it were unbiased). Our integrative framework provides researchers and practitioners with a unique tool that generates numerical answers to questions such as the following: What are the anticipated consequences for bias‐based selection errors of various degrees of test validity and test bias? What are the anticipated consequences for adverse impact of various degrees of test validity and test bias? From a theory point of view, our framework provides a more complete picture of the selection process by integrating 4 key concepts that have not been examined simultaneously thus far. From a practical point of view, our framework provides test developers, employers, and policy makers a broader perspective and new insights regarding practical consequences associated with various selection systems that vary on their degree of validity and bias. We present a computer program available online to perform all needed calculations.