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Author: Frederick L. Oswald Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
In the past 25 years, organizational researchers and practitioners have relied heavily on computer simulation research to understand how group mean differences and correlations affect overall validity and adverse impact in protected groups (e.g., racial/ethnic groups and gender) as they relate to personnel selection practices. We point out a multilevel issue affecting nearly all past simulations: The total correlations that these simulations intended to specify are somewhat distorted after group mean differences were introduced into the data. Although this distorting effect is minimal in most cases, it matters in some cases, and after all, the main virtue of statistical simulations is precision, both in the population parameters and sample data and statistics those parameters are supposed to generate. We demonstrate this distorting effect through one specific example, based on multiple predictors and meta-analytic data, followed by a broader simulation for single predictors across a wide variety of selection conditions. Rather than merely point out this problem, we also provide a straightforward solution: multilevel formulas that incorporate both between- and within-group correlations that always correct for this biasing problem, yielding more accurate simulation results. We conclude by discussing applications and promising extensions of this work.
Author: Frederick L. Oswald Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
In the past 25 years, organizational researchers and practitioners have relied heavily on computer simulation research to understand how group mean differences and correlations affect overall validity and adverse impact in protected groups (e.g., racial/ethnic groups and gender) as they relate to personnel selection practices. We point out a multilevel issue affecting nearly all past simulations: The total correlations that these simulations intended to specify are somewhat distorted after group mean differences were introduced into the data. Although this distorting effect is minimal in most cases, it matters in some cases, and after all, the main virtue of statistical simulations is precision, both in the population parameters and sample data and statistics those parameters are supposed to generate. We demonstrate this distorting effect through one specific example, based on multiple predictors and meta-analytic data, followed by a broader simulation for single predictors across a wide variety of selection conditions. Rather than merely point out this problem, we also provide a straightforward solution: multilevel formulas that incorporate both between- and within-group correlations that always correct for this biasing problem, yielding more accurate simulation results. We conclude by discussing applications and promising extensions of this work.
Author: Michael Fetzer Publisher: Springer Science & Business Media ISBN: 146147681X Category : Psychology Languages : en Pages : 281
Book Description
This book provides a comprehensive and state-of-the-art overview of simulation development, technologies, and implementation, including real-world examples and results followed by a preview of what’s on the horizon that will further revolutionize the industry. More than a handful of books have been written on the use of simulations for training purposes, but this book focuses solely on simulations in employee selection contexts (e.g., hiring, promotion), making it a truly unique and valuable resource for both practitioners and academics. The science and practice of employee selection has advanced at a steady pace over the past two or three decades. However, recent advancements in both technology and assessment methods have been the catalyst for an evolutionary leap in the use of simulations in this area.
Author: Publisher: ISBN: Category : Families Languages : en Pages : 44
Book Description
"Objective: The National Survey of Family Growth (NSFG) collects data on pregnancy, childbearing, men's and women's health, and parenting from a national sample of women and men 15-44 years of age in the United States. This report describes the sample design for the NSFG's new continuous design and the effects of that design on weighting and variance estimation procedures. A working knowledge of this information is important for researchers who wish to use the data. Two data files are being released the first covering 2.5 years (30 months) of data collection and the second after all data have been collected. This report is being released with the first data file. A later report in this Series will include specific results of the weighting, imputation, and variance estimation. Methods: The NSFG's new design is based on an independent, national probability sample of women and men 15-44 years of age. Fieldwork was carried out by the University of Michigan's Institute for Social Research (ISR) under a contract with the National Center for Health Statistics (NCHS). In-person, face-to-face interviews were conducted by professional female interviewers using laptop computers. Results: Analysis of NSFG data requires the use of sampling weights and estimation of sampling errors that account for the complex sample design and estimation features of the survey. Sampling weights are provided on the data files. The rate of missing data in the survey is generally low. However, missing data were imputed for about 600 key variables (called 'recodes') that are used for most analyses of the survey. Imputation was accomplished using a multiple regression procedure with software called IVEware, available from the University of Michigan website."--Page 1.
Author: James L. Outtz Publisher: Taylor & Francis ISBN: 1136948198 Category : Psychology Languages : en Pages : 564
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: Publisher: Department of Health and Human Services Centers for Disease Contr ISBN: Category : Family & Relationships Languages : en Pages : 296
Author: Markus Dirk Dubber Publisher: Oxford Handbooks ISBN: 019006739X Category : Business & Economics Languages : en Pages : 896
Book Description
This interdisciplinary and international handbook captures and shapes much needed reflection on normative frameworks for the production, application, and use of artificial intelligence in all spheres of individual, commercial, social, and public life.
Author: Frederick L. Oswald
Author: Frederick L. Oswald
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Author: James L. Outtz
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Author: Markus Dirk Dubber
Author: Jian Zhang