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Comparing Groups – Randomization and Bootstrap Methods Using R

Autor A Zieffler
en Limba Engleză Hardback – 30 iun 2011
A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences research Computing has become an essential part of the day-to-day practice of statistical work, broadening the types of questions that can now be addressed by research scientists applying newly derived data analytic techniques. Comparing Groups: Randomization and Bootstrap Methods Using R emphasizes the direct link between scientific research questions and data analysis. Rather than relying on mathematical calculations, this book focus on conceptual explanations and the use of statistical computing in an effort to guide readers through the integration of design, statistical methodology, and computation to answer specific research questions regarding group differences. Utilizing the widely-used, freely accessible R software, the authors introduce a modern approach to promote methods that provide a more complete understanding of statistical concepts. Following an introduction to R, each chapter is driven by a research question, and empirical data analysis is used to provide answers to that question. These examples are data-driven inquiries that promote interaction between statistical methods and ideas and computer application. Computer code and output are interwoven in the book to illustrate exactly how each analysis is carried out and how output is interpreted. Additional topical coverage includes: * Data exploration of one variable and multivariate data * Comparing two groups and many groups * Permutation tests, randomization tests, and the independent samples t-Test * Bootstrap tests and bootstrap intervals * Interval estimates and effect sizes Throughout the book, the authors incorporate data from real-world research studies as well aschapter problems that provide a platform to perform data analyses. A related Web site features a complete collection of the book's datasets along with the accompanying codebooks and the R script files and commands, allowing readers to reproduce the presented output and plots. Comparing Groups: Randomization and Bootstrap Methods Using R is an excellent book for upper-undergraduate and graduate level courses on statistical methods, particularlyin the educational and behavioral sciences. The book also serves as a valuable resource for researchers who need a practical guide to modern data analytic and computational methods.
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Specificații

ISBN-13: 9780470621691
ISBN-10: 0470621699
Pagini: 332
Dimensiuni: 168 x 238 x 24 mm
Greutate: 0.61 kg
Editura: Wiley
Locul publicării:Hoboken, United States

Public țintă

Researchers who need a practical guide to modern data analytic and computational methods, undergraduate and first–year graduate students in statistical methods, especially in the educational and behavioral sciences, including developmental psychology, clinical psychology, educational & school psychology, special education, epidemiology, family social science, kinesiology, communication disorders, education policy and administration, etc.; academic libraries

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Notă biografică

Andrew S. Zieffler, PhD, is Lecturer in the Department of Educational Psychology at the University of Minnesota. Dr. Zieffler has published numerous articles in his areas of research interest, which include the measurement and assessment in statistics education research and statistical computing. Jeffrey R. Harring, PhD, is Assistant Professor in the Department of Measurement, Statistics, and Evaluation at the University of Maryland. Dr. Harring currently focuses his research on statistical models for repeated measures data and nonlinear structural equation models. Jeffrey D. Long, PhD, is Professor of Psychiatry in the Carver College of Medicine at The University of Iowa and Head Statistician for Neurobiological Predictors of Huntington's Disease (PREDICT-HD), a longitudinal NIH-funded study of early detection of Huntington's disease. His interests include the analysis of longitudinal and time-to-event data and ordinal data.

Descriere

Emphasizing the direct link between scientific research questions and data analysis, Modern Statistical and Computing Methods for the Behavioral and Educational Sciences Using R introduces current statistical methods, including the use of Monte Carlo simulation, bootstrapping, and randomization tests.