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Statistical Analysis of Adverse Impact

Author: Stephanie R. Thomas

Publisher: Stephanie R. Thomas

Published: 2011

Total Pages: 227

ISBN-13: 1456766228

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 Analysis

Author: Scott B. Morris

Publisher: Psychology Press

Published: 2016-12-01

Total Pages: 381

ISBN-13: 1315301415

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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

A Comparison of Adverse Impact Analysis and Statistical Analysis for Evaluating Group Differences on Written and Oral Selection Procedures

Author: Susan Marie Hough

Publisher:

Published: 1984

Total Pages: 90

ISBN-13:

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Statistical Methods in Discrimination Litigation

Author: Kaye

Publisher: CRC Press

Published: 2014-07-22

Total Pages: 232

ISBN-13: 1498710484

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9. Issues and Methods in Discrimination Statistics -- 9.1. INTRODUCTION -- 9.2. BASIC STATISTICAL CONCEPTS IN THE COURTROOM -- 9.2.1. The Historical Legacy -- 9.2.2. Philosophical Attitudes Towards Probability -- 9.2.3. Hypothesis Tests -- 9.2.4. Confidence Intervals -- 9.2.5. Selection Effects -- 9.3. SPECIFIC STATISTICAL METHODS -- 9.3.1. Multiple Regression -- 9.3.2. Structural Models and Unreliability -- 9.3.3. Multiple Inference -- 9.3.4. Comparison of Rates and Proportions -- 9.3.5. Temporal Analysis -- 9.4. SUMMARY AND CONCLUSIONS -- REFERENCES -- Index

Statistical Methods in Discrimination Litigation

Author: Kaye

Publisher: CRC Press

Published: 1986-08-07

Total Pages: 236

ISBN-13: 9780824775148

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Helping expert witnesses and consultants fulfill their professional responsibility by choosing the best statistical method for specific legal situations, this valuable reference surveys the most common methods already in use, describes their flaws and problems, anticipates significant new difficulties not previously identified, and supports the development and application of more refined techniques suited to the phenomena of discrimination. Statistical Methods in Discrimination Litigation considers the legal theories that underlie the collection and analysis of data for courtroom use ... discusses essential statistical techniques, such as the odds ratio, Mantel-Haenszel test, multiple linear regression analyses, competing psychometric concepts of fairness, and more ... outlines means of improving statistical presentations in court by more sophisticated data analysis techniques ... and brings together materials and references from law, statistics, and psychology in a unique synthesis. Introducing statisticians and social scientists to the legal concepts and methodological issues necessary for proving or rebutting claims of discrimination with statistical evidence, Statistical Methods in Discrimination Litigation is an important reference for applied statisticians; economists; psychologists; sociologists; attorneys and judges involved in discrimination litigation as well as experts who consult or testify in discrimination cases; advanced undergraduate statistics courses; and law school and graduate economics seminars on discrimination. Book jacket.

Adverse Impact Analysis

Author: Scott B. Morris

Publisher: Psychology Press

Published: 2016-12-01

Total Pages: 401

ISBN-13: 1315301423

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Analysis of Safety Data of Drug Trials

Author: Ton J. Cleophas

Publisher: Springer

Published: 2019-02-26

Total Pages: 217

ISBN-13: 3030058042

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In 2010, the 5th edition of the textbook, "Statistics Applied to Clinical Studies", was published by Springer and since then has been widely distributed. The primary object of clinical trials of new drugs is to demonstrate efficacy rather than safety. However, a trial in humans which does not adequately address safety is unethical, while the assessment of safety variables is an important element of the trial. An effective approach is to present summaries of the prevalence of adverse effects and their 95% confidence intervals. In order to estimate the probability that the differences between treatment and control group occurred merely by chance, a statistical test can be performed. In the past few years, this pretty crude method has been supplemented and sometimes, replaced with more sophisticated and better sensitive methodologies, based on machine learning clusters and networks, and multivariate analyses. As a result, it is time that an updated version of safety data analysis was published. The issue of dependency also needs to be addressed. Adverse effects may be either dependent or independent of the main outcome. For example, an adverse effect of alpha blockers is dizziness and this occurs independently of the main outcome "alleviation of Raynaud 's phenomenon". In contrast, the adverse effect "increased calorie intake" occurs with "increased exercise", and this adverse effect is very dependent on the main outcome "weight loss". Random heterogeneities, outliers, confounders, interaction factors are common in clinical trials, and all of them can be considered as kinds of adverse effects of the dependent type. Random regressions and analyses of variance, high dimensional clusterings, partial correlations, structural equations models, Bayesian methods are helpful for their analysis. The current edition was written for non-mathematicians, particularly medical and health professionals and students. It provides examples of modern analytic methods so far largely unused in safety analysis. All of the 14 chapters have two core characteristics, First, they are intended for current usage, and they are particularly concerned with that usage. Second, they try and tell what readers need to know in order to understand and apply the methods. For that purpose, step by step analyses of both hypothesized and real data examples are provided.

Adverse Impact and Test Validation

Author: Dan Biddle

Publisher: Routledge

Published: 2017-05-15

Total Pages: 153

ISBN-13: 135196061X

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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.

Registries for Evaluating Patient Outcomes

Author: Agency for Healthcare Research and Quality/AHRQ

Publisher: Government Printing Office

Published: 2014-04-01

Total Pages: 396

ISBN-13: 1587634333

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This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.