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Author: Stephanie R. Thomas
Publisher: Stephanie R. Thomas
ISBN: 1456766228
Category : Business & Economics
Languages : en
Pages : 227
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Book Description
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.
Author: Stephanie R. Thomas
Publisher: Stephanie R. Thomas
ISBN: 1456766228
Category : Business & Economics
Languages : en
Pages : 227
Get Book Here
Book Description
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.
Author: Scott B. Morris
Publisher: Psychology Press
ISBN: 1315301415
Category : Business & Economics
Languages : en
Pages : 381
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Book Description
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
Author: Susan Marie Hough
Publisher:
ISBN:
Category : Employee selection
Languages : en
Pages : 90
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Book Description
Author: D.H. Kaye
Publisher: CRC Press
ISBN: 1498710484
Category : Mathematics
Languages : en
Pages : 233
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Book Description
This book sketches some of the legal doctrines that underlie discrimination litigation. It describes and probes frequently seen statistical methods. The book also describes the more or less standard methods being brought into United States Supreme Court.
Author: Scott B. Morris
Publisher: Psychology Press
ISBN: 1315301423
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
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
Author: Ton J. Cleophas
Publisher: Springer
ISBN: 3030058042
Category : Medical
Languages : en
Pages : 217
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Book Description
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.
Author: James L. Outtz
Publisher: Routledge
ISBN: 113694818X
Category : Psychology
Languages : en
Pages : 616
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Book Description
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.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309091268
Category : Social Science
Languages : en
Pages : 335
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Book Description
Many racial and ethnic groups in the United States, including blacks, Hispanics, Asians, American Indians, and others, have historically faced severe discriminationâ€"pervasive and open denial of civil, social, political, educational, and economic opportunities. Today, large differences among racial and ethnic groups continue to exist in employment, income and wealth, housing, education, criminal justice, health, and other areas. While many factors may contribute to such differences, their size and extent suggest that various forms of discriminatory treatment persist in U.S. society and serve to undercut the achievement of equal opportunity. Measuring Racial Discrimination considers the definition of race and racial discrimination, reviews the existing techniques used to measure racial discrimination, and identifies new tools and areas for future research. The book conducts a thorough evaluation of current methodologies for a wide range of circumstances in which racial discrimination may occur, and makes recommendations on how to better assess the presence and effects of discrimination.
Author: Elizabeth J. Howard
Publisher:
ISBN:
Category :
Languages : en
Pages : 234
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Book Description
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309316324
Category : Medical
Languages : en
Pages : 236
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Book Description
Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
