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
Table of Contents:
Section 1. Introduction 1.An Introduction to Adverse Impact Measurement in the EEO Context Eric M. Dunleavy and Scott B. Morris 2. Understanding Employment Data used for EEO Disparity Analyses David P. Lamoreaux and Matthew R. Thompson Section 2. Analyzing Employee Selection Decisions 3. Structuring a Traditional EEO Adverse Impact Analysis: The 2×2 Table David Cohen, David S. Fortney, and Emilee Tison 4. Statistical Significance Testing in Adverse Impact Analysis Scott B. Morris 5. Measuring Practical Significance in Adverse Impact Analysis Fred Oswald, Eric M. Dunleavy, and Amy Shaw 6. When and Why do Different Indices Lead to Different Conclusions about Adverse Impact Kevin Murphy and Rick Jacobs 7. Workforce Composition and Utilization Analyzes Dan Kuang and Marife Ramos 8. Many 2×2 Tables: Understanding Multiple Events in Adverse Impact Analyses Scott B. Morris, Eric M. Dunleavy, and Mirinae Lee Section 3. Analyzing Other Employment Outcomes 9. Proper Methods for Statistical Analysis of Promotions Bernard Siskin and Nicholas Schmidt 10. Analyzing EEO Disparities in Pay: A Primer on Structuring Analyses Dennis Doverspike, Winfred Arthur, Jr., and Catalina Flores 11. Analyzing EEO Disparities in Pay: Guidance in the Application of Regression Analyses Kayo Sady and Michael Aamodt 12. Analyzing Reduction in Force and Other Termination Decisions Donald R. Deere and James E. Pearce Section 4. Perspectives on Adverse Impact Analysis 13. Using Your Data Wisely: Proactive Monitoring of Employment Disparities Kathleen K. Lundquist, Toni S. Locklear, and Michael Lippstreu 14.Thoughts from an EEO Agency Perspective Richard Tonowski 15. Addressing the Ever Increasing Standards for Statistical Evidence: A Plaintiff Attorney's Perspective Cyrus Mehri and Michael Lieder 16. Disparate Impact, Trial by Statistics: Thoughts from a Defense Attorney's Perspective David Bennet Ross and Gina Merrill 17. Case Law Interpretations of Statistical Evidence Regarding Adverse Impact Arthur Gutman 18. Some Conclusions and Emerging Issues in Adverse Impact Measurement Eric M. Dunleavy amd Scott B. Morris
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.
Review :
"I recommend that any industrial–organizational or HR practitioner have a copy of this book on hand as it will not only provide most of the answers to your adverse-impact questions but will also provide guidance on topics that you did not know you needed guidance on."
- Kyle Morgan, Associate Consultant, Aon, Philadelphia, PA
