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Handbook of Ethics in Quantitative Methodology
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Table of Contents

Ethics in Quantitative Methodology: An Introduction. Part 1: Developing an Ethical Framework for Methodologists. Ethics in Quantitative Professional Practice. Ethical Principles in Data Analysis: An Overview. Part 2: Teaching Quantitative Ethics. A Statistical Guide for the Ethically Perplexed. Part 3: Ethics and Research Design Issues. Measurement Choices: Reliability, Validity, and Generalizability. Ethics and Sample Size Planning. Ethics and the Conduct of Randomized Experiments and Quasi-Experiments in Field Settings. Psychometric Methods and High-Stakes Assessment: Contexts and Methods for Ethical Testing Practice. Ethics in Program Evaluation. Part 4: Ethics and Data Analysis Issues. Beyond Treating Complex Sampling Designs as Simple Random Samples: Data Analysis and Reporting. From Hypothesis Testing to Parameter Estimation: An Example of Evidence-Based Practice in Statistics. Some Ethical Issues in Factor Analysis. Ethical Aspects of Multilevel Modeling. The Impact of Missing Data on the Ethical Quality of a Research Study. The Science and Ethics of Causal Modeling. Part 5: Ethics and Communicating Findings. Ethical Issues in the Conduct and Reporting of Meta-Analysis. Ethics and Statistical Reform: Lessons from Medicine. Ethical Issues in Professional Research, Writing, and Publishing.

About the Author

A.T. Panter is the Bowman and Gordon Gray Distinguished Professor of Psychology at the L.aL. Thurstone Psychometric Laboratory at University of North Carolina, Chapel Hill. She develops instruments, research designs, and data-analytic strategies for applied research questions in health and education. Her publications are in survey methodology, measurement and testing, advanced quantitative methods, program evaluation, and individual differences. She has received numerous teaching awards including APA's Jacob Cohen Award for Distinguished Contributions to Teaching and Mentoring. She has significant national service in disability assessment, testing in higher education, women in science, and the advancement of quantitative psychology. Sonya K. Sterba is an Assistant Professor in the Quantitative Psychology Program at Vanderbilt University. She received her Ph.D. in Quantitative Psychology and her M.A. in Child Clinical Psychology from the University of North Carolina at Chapel Hill. Her research evaluates how traditional structural equation and multilevel models can be adapted to handle methodological issues that arise in developmental psychopathology research.

Reviews

"A timely book that fills a notable void -- highlighting ethical issues that arise in applying quantitative techniques. Leading researchers have written engaging chapters that probe matters often given less-than-adequate emphasis. A 'must read' for graduate students and professionals alike." -- Keith F. Widaman, University of California at Davis, USA "The editors have assembled an impressive panel of contributors. This timely treatment of an important topic is sure to have a prominent place on the shelf of anyone who mentors graduate students or serves as a statistical consultant." - Linda M. Collins, The Pennsylvania State University, USA "This remarkable volume brings together experts who write about best-practice use of quantitative methods that will promote competence and therefore ethical use of these methods.aI consider this Handbook to beaessential reading for researchers who aim to demonstrate their integrityain the post-modernist era of science." - Patrick E. Shrout, New York University, USA "An original and informative volume that is filled with good advice to help make better choices about research design, data analysis, and the communication of research findings." - Debbie S. Moskowitz, McGill University, Canada "This book could be one of the most exciting to emerge in our field for many years, and could set the stage for a whole movement of attention toward treatment of ethical issues in Quantitative Psychology." -Joe Rodgers, University of Oklahoma, USA "The faulty identification or failure to identify risk factors, treatments, and adverse events is consequential for the people we treat. If the fault is the result of outmoded methods that could be avoided, there is an ethical issue. !This book will be one of a kind. !I will require this book in my intro graduate statistics class." -William F. Chaplin, St. John's University, USA "There is need to draw on an ethical framework to motivate the accelerated use of the newer or most appropriate methods. In fact, this may be a key ingredient in [preventing]! social scientists from being dismissive of the need to understand issues in their methods classes.! As a resource for journal editors and other quantitatively oriented researchers, this book would be of general interest." -Scott M. Hofer, University of Victoria, Canada

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