Adverse Impact Analysis: Understanding Data, Statistics, and Risk

Scott B. Morris, Eric M. Dunleavy

ISBN 10: 1138855847 / ISBN 13: 9781138855847

Published by Routledge 2017-01-22, 2017

About this Item

Seller Inventory # 6666-TNFPD-9781138855847

Bibliographic Details

• Title: Adverse Impact Analysis: Understanding Data, Statistics, and Risk
• Publisher: Routledge 2017-01-22
• Publication Date: 2017
• Language: English
• ISBN 10: 1138855847
• ISBN 13: 9781138855847
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Compliance with federal equal employment opportunity regulations, including civil rights laws and affirmative action requirements, requires collection and analysis of data on disparities in employment outcomes, often referred to as adverse impact. While most human resources (HR) practitioners are familiar with basic adverse impact analysis, the courts and regulatory agencies are increasingly relying on more sophisticated methods to assess disparities. Employment data are often complicated, and can include a broad array of employment actions (e.g., selection, pay, promotion, termination), as well as data that span multiple protected groups, settings, and points in time. In the era of "big data," the HR analyst often has access to larger and more complex data sets relevant to employment disparities. Consequently, an informed HR practitioner needs a richer understanding of the issues and methods for conducting disparity analyses.

This book brings together the diverse literature on disparity analysis, spanning work from statistics, industrial/organizational psychology, human resource management, labor economics, and law, to provide a comprehensive and integrated summary of current best practices in the field. Throughout, the description of methods is grounded in the legal context and current trends in employment litigation and the practices of federal regulatory agencies.

The book provides guidance on all phases of disparity analysis, including:

• How to structure diverse and complex employment data for disparity analysis
• How to conduct both basic and advanced statistical analyses on employment outcomes related to employee selection, promotion, compensation, termination, and other employment outcomes
• How to interpret results in terms of both practical and statistical significance
• Common practical challenges and pitfalls in disparity analysis and strategies to deal with these issues

About the Author

Scott B. Morris, Ph.D., is a professor of industrial/organizational psychology at Illinois Institute of Technology. Much of his work focuses on applied data analysis issues in personnel selection, including adverse impact analysis, test bias analysis, and test validation.

Eric M. Dunleavy, Ph.D., is the director of the Personnel Selection and Litigation Support Services department at DCI Consulting Group. His primary areas of expertise are in employee selection, validation research, adverse impact analyses, and other EEO analytics.