no information available
Best Practices in Quantitative Methods follows the tradition of handbooks in that it calls on the top researchers in the field tshare with us what they know In this case, the focus of the chapters is on best practices for the vast field of quantitative methods The volume provides readers with the most effective, evidence-based ways tuse and analyze quantitative methods and quantitative data across the social and behavioral sciences and education The text is divided intthree main sections: Basics of Best Practices, in which a comprehensive review of basic statistic and methodological practices is covered, including core statistical methods and critical data analysis issues such as power, effect sizes, and assumptions; Advanced Best Practices, leading with logistic regression, and moving through IRT, Rasch Measurement, HLM, Meta-Analysis, and the inimitable area of Sampling; and The Implications of Best Practices, including a discussion of the ethical implications of quantitative analysis 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-rangning examples along with any empirical evidence tshow why certain techniques are better The book encourages best practices in three very distinct ways: 1) Some chapters will describe important implicit knowledge treaders For example, one of the most common data transformations is the square root transformation Statistics and quantitative methods are filled with examples of these seemingly mundane aspects of research life that makes a substantial difference Chapters in this book gather the important details, make them accessible treaders, and demonstrate why it is important tpay attention tthese details 2) Other chapters compare and contrast analytic techniques tgive readers information they need tdecide the best way tanalyze particular data For example, exploratory factor analysis has up teight extraction methods, several rotation options, multiple ways tdecide how many factors you have, and it is often the case that the options are not clearly described or discussed Some of the chapters will examine instances where there are multiple options for doing things, and make recommendations as twhat the ôbestö choice (or choices, as what is best often depends on the circumstances) are 3) Finally, there are always new procedures being developed and disseminated Many times (not all) newer procedures represent improvements over old procedures Some chapters will present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how tperform them, and demonstrating their useThis book is an invaluable resource for graduate students and researchers whwant a comprehensive, authoritative resource tgtfor practical and sound advice from leading experts in quantitative methods
