The contributors to
Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor
Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences.
The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better.
Key Features: - Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details.
- Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice―or choices, as what is best often depends on the circumstances.
- Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use.
Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
Jason W. Osborne is a thought leader and professor in higher education. His background in educational psychology, statistics and quantitative methods, along with that gleaned from high-level positions within Academia gives a unique perspective on the real-world data factors. In 2015, he was appointed Associate Provost and Dean of the Graduate School at Clemson University in Clemson, South Carolina. As well as Associate Provost, at Clemson University, Jason was a Professor of applied statistics at the School of Mathematical Sciences, with a secondary appointment in Public Health Science. In 2019, he took on the role of Provost and Executive VP for Academic Affairs at Miami University. As Provost, Jason implemented a transformative strategic plan to reposition the institution as one prepared for new challenges with a modern, compelling curriculum, a welcoming environment, and enhanced support for student faculty positions and staff. In 2021, he was named by Stanford University as one of the top 2% researchers in the world, underlining his commitment to world-class research methods across particular domains, ultimately influencing a generation of learners. Currently, Jason teaches and publishes on data analysis "best practices" in quantitative and applied research methods. He has served as evaluator or consultant on research projects and in public education (K-12), instructional technology, health care, medicine and business. He served as founding editor of Frontiers in Quantitative Psychology and Measurement and has been on the editorial boards of several other journals (such as Practical Assessment, Research, and Evaluation). Jason W Osborne also publishes on identification with academics and on issues related to social justice and diversity. He has written seven books covering topics to communicate logistic regression and linear modeling, exploratory factor analysis, best practices and modern research methods, data cleaning, and numerous other topics.
