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

Written with human resources professionals, in-house counsel and employment lawyers in mind, readers are introduced to the statistical analysis of adverse impact. Various tools for examining disparate impact are presented in a non-technical manner. Concrete examples and simple calculations demonstrate how these statistical tools can be applied to questions of adverse impact in hiring, promotion, and termination decisions. Traditional areas of vulnerability to adverse impact are discussed, and some emerging areas with potential for adverse impact, such as the use of social media in recruiting and current employment status as a candidate screening tool, are presented. The underlying sources of vulnerability are explored and pending legislation is discussed. The importance of litigation avoidance is stressed, and suggestions for minimizing the risk of employment litigation with proactive statistical analysis are provided. The goal is to give human resources professionals and legal counsel a better understanding of the information their statistical consultants are providing. This leads to an improved ability to identify and correct problem areas that may exist within the organization, as well as to prevent problems from arising in the future.

Adverse impact analyses and test validation promote social justice and equity. Employers who unknowingly use invalid tests or recruitment procedures that have an adverse impact are reducing minority and/or female representation in their workforce, unfairly screening out qualified workers and (worst of all) just plain discriminating. Dan Biddle's Adverse Impact and Test Validation provides you with analyses that allow you to identify which of your selection procedures have adverse impact. The validation steps will help you decide whether to keep the selection procedure (because it's valid), change it, or stop using it altogether. This second edition contains new material on using multiple regression to evaluate pay practices and provides step-by-step instructions for using SPSS or Excel for evaluating your company's pay practices for possible inequities. New content on how to define "Internet applicants" and set up defensible Basic Qualifications (BQs) for online recruiting will help employers ensure compliance with EEO regulations and screen in qualified applicants. Specific guidelines for developing and validating written job knowledge tests, such as those used for police and fire promotional testing, have also been included in this new edition. The downloadable resources include tools (which may be used on a trial evaluation basis) describing several of the functions described in the book, including Adverse Impact Toolkit®, Test Validation and Analysis Program® (TVAP®), Guidelines Oriented Job Analysis® (GOJA®) Manual, and Content Validity Checklists. This highly pragmatic guide goes beyond the concepts, theories and ideas behind adverse impact and test validation. It not only explains what to do but crucially, also shows you how to do it. The second edition has been expanded to include two brand new chapters with a new Appendix and comes with new editions of the accompanying software. As a means of protecting your organization from litigation, damage to employee relations and to your corporate reputation, Adverse Impact and Test Validation is a 'must-have' purchase for human resource professionals, testing and recruitment specialists.

This text is the best single repository for a comprehensive examination of the scientific research and practical issues associated with adverse impact. Adverse impact occurs when there is a significant difference in organizational outcomes to the disadvantage of one or more groups defined on the basis of demographic characteristics such as race, ethnicity, gender, age, religion, etc. This book shows, based on scientific research, how to design selection systems that minimize subgroup differences. The primary object of this volume in the SIOP series is to bring together renowned experts in this field to present their viewpoints and perspectives on what underlies adverse impact, where we are in terms of assessing it and what we may have learned (or not learned) about minimizing it.

This book provides a practical, hands-on framework for EEO analyses and test validation, making it an invaluable resource for HR professionals and legal practitioners who are responsible for pre-employment testing, hiring, and promotion.

This text is the best single repository for a comprehensive examination of the scientific research and practical issues associated with adverse impact. Adverse impact occurs when there is a significant difference in organizational outcomes to the disadvantage of one or more groups defined on the basis of demographic characteristics such as race, ethnicity, gender, age, religion, etc. This book shows, based on scientific research, how to design selection systems that minimize subgroup differences. The primary object of this volume in the SIOP series is to bring together renowned experts in this field to present their viewpoints and perspectives on what underlies adverse impact, where we are in terms of assessing it and what we may have learned (or not learned) about minimizing it.

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